Mathematics Books

Book SynopsisThis book addresses the most efficient methods of pattern analysis using wavelet decomposition. Readers will learn to analyze data in order to emphasize the differences between closely related patterns and then categorize them in a way that is useful to system users.Trade Review"...provides a valuable summary of data reduction." (Technometrics, May 2002) "...effectively describes and summarizes an emerging new field, namely, scientific data modeling and analysis." (Mathematical Reviews, 2003h)Table of ContentsPreface. Acknowledgments. INTRODUCTION. Pattern Analysis as Data Reduction. Vector Spaces and Linear Transformations. OPTIMAL ORTHOGONAL PATTERN REPRESENTATIONS. The Karhunen-Loève Expansion. Additional Theory, Algorithms and Applications. TIME, FREQUENCY AND SCALE ANALYSIS. Fourier Analysis. Wavelet Expansions. ADAPTIVE NONLINEAR MAPPINGS. Radial Basis Functions. Neural Networks. Nonlinear Reduction Architectures. Appendix A Mathemetical Preliminaries. References. Index.

Read more less

Book SynopsisA timely book on a topic that has witnessed a surge of interest over the last decade, owing in part to several novel applications, most notably in data compression and computational molecular biology. It describes methods employed in average case analysis of algorithms, combining both analytical and probabilistic tools in a single volume.Trade Review"Surveying the major techniques of average case analysis, this graduate textbook presents both analytical methods used for well-structured algorithms and probabilistic methods used for more structurally complex algorithms." (SciTech Book News, Vol. 25, No. 3, September 2001) "...contains a comprehensive treatment on probabilistic, combinatorial, and analytical techniques and methods...treatment is clear, rigorous, self-contained, with many examples and exercises." (Zentralblatt MATH Vol. 968, 2001/18) "This well-organized book...is certainly useful...It is a valuable source for a deeper and more precise understanding of the behaviors of algorithms on sequences." (Mathematical Reviews, 2002f)Table of ContentsForeword. Preface. Acknowledgments. PROBLEMS ON WORDS. Data Structures and Algorithms on Words. Probabilistic and Analytical Models. PROBABILISTIC AND COMBINATORIAL TECHNIQUES. Inclusion-Exclusion Principle. The First and Second Moment Methods. Subadditive Ergodic Theorem and Large Deviations. Elements of Information Theory. ANALYTIC TECHNIQUES. Generating Functions. Complex Asymptotic Methods. Mellin Transform and Its Applications. Analytic Poissonization and Depoissonization. Bibliography. Index.

Read more less

Book SynopsisThrough its presentation of the essentials, this text is briefer than some and has been carefully edited and designed to meet the specific needs of a one-semester course at the appropriate level for a Senior.Following extensive student testing for readability and understandability, examples have been intermixed with the theory throughout the book to introduce, motivate, and extend the main text. Although readability is emphasized, proofs are provided to promote logical thinking. Finally, the author''s conversational style holds the reader''s interest while exploring several important topics that traditionally have been reserved for graduate courses. The result is that students can apply theory that is sometimes a sterile subject in other courses, and can hit the ground running in advanced courses in feedback control design, dynamics of power systems, communications, and signal processing.Trade Review"...an excellent collection of examples...a good addition to the field of linear systems..." (Int Jnl of Robust & Nonlinear Control, May 2002)Table of ContentsSolution of State-Space Equations. Transform Methods. Writing State-Space Equations. Matrices Over a Field. Vector Spaces. Similarity Transformations. Stability. Minimality via Similarity Transformations. Poles and Zeros. References. Appendix. Index.

Read more less

Book SynopsisOne of the most striking applications of chaos theory in recent years, non-linear pricing uses genetic algorithms, fuzzy logic, fractal imaging and other cutting-edge technologies to identify and exploit patterns hidden within the seemingly helter-skelter rise and fall of daily stock prices.Trade Review"A lively and intriguing book from a writer who can range from Zen to mathematics."-Adam Smith, author of The Money Game and Paper Money "Nonlinear Pricing is an eminently readable book which I found satisfied both the theorist and the practitioner in me. For the theorist, there are new insights into the relationship between complexity and the markets. For the practitioner, there are practical ideas on how to fashion investment strategies. I highly recommend Nonlinear Pricing to all students of the markets."-Edgar E. Peters, Chief Investment Strategist, PanAgora Asset Management; author, Chaos and Order in the Capital Markets "Nonlinear Pricing goes further than any book I am aware of in drawing a connection between the real world of economics and the new ideas about economics coming from the science of self-organized systems. Written in a lively, informal style, this is a wonderful read for those of us who have been wondering whether anyone understands anything at all about how markets work."-Lee Smolin, PhD, Department of Physics, Pennsylvania State University "Required reading for the enlightened financial professional. Enjoyable for the intelligent investor. A dash of physics, bite-sized pieces of nonlinear concepts, and a broth of hands-on experience make this a cookbook for the modern trader."-Richard E. Morley, Potts Medal recipient and founder of the Breakfast Club "A real eye-opener-Nonlinear Pricing explains a complex subject in easy terms and makes the reader aware of the many opportunities offered by this new technology." -Richard Olsen, founder, Olsen and Associates, Zurich "I, of course, think highly of this book as it credits Dance of the Money Bees with inventing 'swarm theory', now a discipline in computer science. There are many other splendid insights." -John Train, author and President of the Montrose Fund "An extraordinary tour d'horizon, this book challenges conventional thinking about finance, investing, and much else besides. Brimming with ideas and eye-opening connections, it makes a powerful case for our need to understand the extent to which nonlinearity shapes our lives." -Andrew Freeman, Managing Editor, Financial Services, The Economist Intelligence Unit; co-author, Seeing Tomorrow: Rewriting the Rules of Risk "Nonlinear Pricing: Theory & Application by Christopher T. May makes nice reading even for people like me who are not economists. This is an ambitious book as it presents economics starting from fundamental physics. It deserves a large readership." -Ilya Prigogine, 1977 Nobel Laureate, Chemistry; author, The End of Certainty; and the world's foremost non-equilibrium scientistTable of ContentsA Toy Story for Wall Street. Nonlinearity: A Retrospective. Nonlinearity: A Prospective. Fractal Analysis. Results of the Hurst Exponent. Nonlinear Technology. Biology and the S&P. Father Time. Nonlinear Pricing-Advanced Concepts. The Last Word-Resonance. Appendix. Glossary. Bibliography. Index.

Read more less

Book SynopsisAn accessible, clearly organized survey of the basic topics of measure theory for students and researchers in mathematics, statistics, and physics In order to fully understand and appreciate advanced probability, analysis, and advanced mathematical statistics, a rudimentary knowledge of measure theory and like subjects must first be obtained.Trade Review"…an excellent read…I was impressed with the wealth of information and the amount of flawless detail." (Journal of the American Statistical Association, March 2006) “…contains many really good exercises…the style is clear and the notation appropriate…” (Zentralbaltt MATH, May 2005)Table of ContentsPreface. Acknowledgments. 1. Set Systems. 2. Measures. 3. Extensions of Measures. 4. Lebesgue Measure. 5. Measurable Functions. 6. The Lebesgue Integral. 7. Integrals Relative to Lebesgue Measure. 8. The Lp Spaces. 9. The Radon–Nikodym Theorem. 10. Products of Two Measure Spaces. 11. Arbitrary Products of Measure Spaces. References. Index.

Read more less

Book SynopsisParallel algorithms Made Easy The complexity of today''s applications coupled with the widespread use of parallel computing has made the design and analysis of parallel algorithms topics of growing interest. This volume fills a need in the field for an introductory treatment of parallel algorithms-appropriate even at the undergraduate level, where no other textbooks on the subject exist. It features a systematic approach to the latest design techniques, providing analysis and implementation details for each parallel algorithm described in the book. Introduction to Parallel Algorithms covers foundations of parallel computing; parallel algorithms for trees and graphs; parallel algorithms for sorting, searching, and merging; and numerical algorithms. This remarkable book: * Presents basic concepts in clear and simple terms * Incorporates numerous examples to enhance students'' understanding * Shows how to develop parallel algorithms for all classical problems in compuTrade Review"...an introduction to parallel algorithms..." (Zentralblatt fur Mathematik, Vol. 948, No. 23)Table of ContentsFOUNDATIONS OF PARALLEL COMPUTING. Elements of Parallel Computing. Data Structures for Parallel Computing. Paradigms for Parallel Algorithm. Simple Algorithms. ALGORITHMS FOR GRAPH MODELS. Tree Algorithms. Graph Algorithms. NC Algorithms for Chordal Graphs. ARRAY MANIPULATION ALGORITHMS. Searching and Merging. Sorting Algorithms. NUMERICAL ALGORITHMS. Algebraic Equations and Matrices. Differentiation and Integration. Differential Equations. Answers to Selected Exercises. Index.

Read more less

Book SynopsisExceptionally well-written, with engaging historical and bibliographic notes, Methods of Geometry sets serious competition to similar titles in the field. It downplays the theory while emphasizing a practical, accessible, proof-oriented approach.Trade Review"It should be emphasized that the book is filled with historicaland bibliographic notes, good motivations and a number ofexercises. Altogether, it can be regarded as a good approach to aspecial part of geometry on an intermediate level." (ZentralblattMath, Volume 955, No 5, 2001) "Fine interweaving of history, foundations, and geometry.... Usefulas a source of exercises." (American Mathematical Monthly, November2001)Table of ContentsFoundations. Elementary Euclidean Geometry. Exercises on Elementary Geometry. Some Triangle and Circle Geometry. Plane Isometries and Similarities. Three Dimensional Isometries and Similarities. Symmetry. Appendices. Bibliography. Index.

Read more less

Book SynopsisA unique, integrated treatment of computer modeling and simulation The future of science belongs to those willing to make the shift to simulation-based modeling, predicts Rice Professor James Thompson, a leading modeler and computational statistician widely known for his original ideas and engaging style. He discusses methods, available to anyone with a fast desktop computer, for integrating simulation into the modeling process in order to create meaningful models of real phenomena. Drawing from a wealth of experience, he gives examples from trading markets, oncology, epidemiology, statistical process control, physics, public policy, combat, real-world optimization, Bayesian analyses, and population dynamics. Dr. Thompson believes that, so far from liberating us from the necessity of modeling, the fast computer enables us to engage in realistic models of processes in , for example, economics, which have not been possible earlier because simple stochastic models in the forward temporal Trade ReviewWith the advent of faster computers with comparatively large storage facilities, simulation-based modeling is rapidly being adopted as an alternative approach to conventional top-down, assumptions-based, continuous, stochastic and discrete differential equation modeling. Thompson offers an interesting exposition to the art of simulation, and views "simulation approach" to modeling as a paradigm for realistic evolutionary modeling. The book is written in a very casual style, and background knowledge in statistics is all that is required to grasp the material contained therein. Thompson begins with an exposition of the generation of randomnumbers and then delves into a variety of special topics, including models for stocks and derivatives, optimization and estimation in a noisy world, Monte-Carlo solutions to differential equations, simulation assessment of multivariate and robust procedures in statistical process control, resampling-based tests, and some exposition to modeling the AIDS epidemic. Several useful algorithms, problem sets, and references to standard simulation packages are provided. Short chapter bibliographies; wide range of examples. The book could be used as a resource for beginning graduate students and professionals in applied statistics, computer science, economics and finance, engineering, and the natural sciences. Highly recommended. Graduate students; faculty; professionals. (CHOICE, April 2001, Vol. 38, No. 8) "...an eclectic survey of computing methods...lively and interesting...the wide variety of example certainly helps bring the material to life." (Journal of the American Statistical Association, Vol. 97, No. 457, March 2002) "...a very useful and entertaining book...a great reference book...contains some valuable material and philosophy that is unavailable anywhere else." (IIE Transactions) "...often entertaining...the level of detain and relevance is appropriate...a worthwhile read for model builders comfortable with both mathematics and simulation." (Complexity, Vol. 7, No. 2, 2002)Table of ContentsThe Generation of "Random" Numbers. Random Quadrature. Monte Carlo Solutions of Differential Equations. Markov Chains, Poisson Processes and Linear Equations. SIMEST, SIMDAT, and Pseudoreality. Models for Stocks and Derivatives. Simulation Assessment of Multivariate and Robust Procedures in Statistical Process Control. Noise and Chaos. Bayesian Approaches. Resampling Based Tests. Optimization and Estimation in a Noisy World. Modeling the USA AIDS Epidemic: Exploration, Simulation and Conjecture. Appendices. Index.

Read more less

Book SynopsisFor Finance and Treasury professionals to effectively pitch, sell,and comprehend the true appeal and relevance of a particularsecurity, there is nothing more important than knowing how thevalue of said security has been determined. While punching numbersinto a computer may provide the information needed, it isnevertheless essential to have a firm grasp of the valuationconcepts in order to make the best, most informed decisions.Offering a straightforward, accessible approach not found anywhereelse, this comprehensive new book provides a clear-cut road mapthrough the mathematical concepts associated with the investmentssector of Treasury management. Written by an expert in the field, Investment Mathematics forFinance and Treasury Professionals explains the principles andformulae used in the fixedincome cash markets. It presents anin-depth, yet practical look at the applications associated withthese money and capital markets instruments. The book also coverscalculations and appliTable of ContentsInstruments in the Band. The Concept of Yield. Yield Spread Analysis. Price/Yield Sensitivity. Term Structure of Interest Rates. Securities with Contingent Cash Flows. Interest Rate Futures Contracts. Foreign Exchange. Options. Exotic Options, Interest Rate Swaps, and Other Interest RateDerivatives. Risk/Return. Information Location. Appendices. Glossary. Index.

Read more less

Book SynopsisThis concise summary of the statistical methods used in the analysis of survival data with censoring emphasizes recently developed nonparametric techniques; outlines methods in detail and illustrates them with actual data; discusses the theory behind each method; and includes numerous worked problems and numerical exercises.Table of ContentsIntroduction to Survival Concepts. Parametric Models. Nonparametric Methods: One Sample. Nonparametric Methods: Two Samples. Nonparametric Methods: K Samples. Nonparametric Methods: Regression. Goodness of Fit. Miscellaneous Topics. Problems. References. Index.

Read more less

Book SynopsisThe sampling inspection tables presented in this book were developed for use in the manufacture of communication apparatus and equipment for the Bell Telephone System. It assembles under one cover the three papers of original publication and adds a brief introduction. The papers have been reproduced with no modifications but the material has been rearranged in chapters. Chapter 1 outlines some of the factors to be considered in setting up inspection plans and develops a basis for minimizing the amount of inspection. Chapter 2 covers double sampling, the average outgoing quality limit (AOQL) concept, and the mathematical background of the tables. Chapter 3 is a reproduction by permission, which outlines the shop procedures for applying the tables.Table of ContentsA Method of Sampling Inspection. Single Sampling and Double Sampling Inspection Tables. Using Double Sampling Inspection in a Manufacturing Plant. Operating Characteristics of Sampling Plans. Appendices. Index.

Read more less

Book SynopsisThis book is about the philosophy and practice of Evolutionary Operation (called EVOP for short), a simple but powerful statistical tool with wide application in industry.Table of ContentsThe Basic Ideas. Simple Statistical Principles on Which EVOP is Based. The 2^2 and 2^3 Factorial Designs. Worksheets for Two-Variable EVOP Programs. Worksheets for Three-Variable EVOP Programs. Some Aspects of the Organization of Evolutionary Operation. EVOP, Optimization, and Variations of EVOP. Comments and Questions on EVOP. Appendices. Tables. References and Bibliography. Index.

Read more less

Book SynopsisA complete guide to the theory and practical applications of probability theory An Introduction to Probability Theory and Its Applications uniquely blends a comprehensive overview of probability theory with the real-world application of that theory. Beginning with the background and very nature of probability theory, the book then proceeds through sample spaces, combinatorial analysis, fluctuations in coin tossing and random walks, the combination of events, types of distributions, Markov chains, stochastic processes, and more. The book''s comprehensive approach provides a complete view of theory along with enlightening examples along the way.Table of ContentsIntroduction: The Nature of Probability Theory. The Sample Space. Elements of Combinatorial Analysis. Fluctuations in Coin Tossing and Random Walks. Combination of Events. Conditional Probability. Stochastic Independence. The Binomial and Poisson Distributions. The Normal Approximation to the Binomial Distribution. Unlimited Sequences of Bernoulli Trials. Random Variables; Expectation. Laws of Large Numbers. Integral Valued Variables. Generating Functions. Compound Distributions. Branching Processes. Recurrent Events. Renewal Theory. Random Walk and Ruin Problems. Markov Chains. Algebraic Treatment of Finite Markov Chains. The Simplest Time-Dependent Stochastic Processes. Answers to Problems.

Read more less

Book SynopsisThe classic text for understanding complex statistical probability An Introduction to Probability Theory and Its Applications offers comprehensive explanations to complex statistical problems. Delving deep into densities and distributions while relating critical formulas, processes and approaches, this rigorous text provides a solid grounding in probability with practice problems throughout. Heavy on application without sacrificing theory, the discussion takes the time to explain difficult topics and how to use them. This new second edition includes new material related to the substitution of probabilistic arguments for combinatorial artifices as well as new sections on branching processes, Markov chains, and the DeMoivre-Laplace theorem.Table of ContentsChapter I The Exponential and the Uniform Densities 1. Introduction 2. Densities. Convolutions 3. The Exponential Density 4. Waiting Time Paradoxes. The Poisson Process 5. The Persistence of Bad Luck 6. Waiting Times and Order Statistics 7. The Uniform Distribution 8. Random Splittings 9. Convolutions and Covering Theorems 10. Random Directions 11. The Use of Lebesgue Measure 12. Empirical Distributions 13. Problems for Solution Chapter II Special Densities. Randomization 1. Notations and Conventions 2. Gamma Distributions 3. Related Distributions of Statistics 4. Some Common Densities 5. Randomization and Mixtures 6. Discrete Distributions 7. Bessel Functions and Random Walks 8. Distributions on a Circle 9. Problems for Solution Chapter III Densities in Higher Dimensions. Normal Densities and Processes 1. Densities 2. Conditional Distributions 3. Return to the Exponential and the Uniform Distributions 4. A Characterization of the Normal Distribution 5. Matrix Notation. The Covariance Matrix 6. Normal Densities and Distributions 7. Stationary Normal Processes 8. Markovian Normal Densities 9. Problems for Solution Chapter IV Probability Measures and Spaces 1. Baire Functions 2. Interval Functions and Integrals in Rr 3. σ-Algebras. Measurability 4. Probability Spaces. Random Variables 5. The Extension Theorem 6. Product Spaces. Sequences of Independent Variables 7. Null Sets. Completion Chapter V Probability Distributions in Rr 1. Distributions and Expectations 2. Preliminaries 3. Densities 4. Convolutions 5. Symmetrization 6. Integration by Parts. Existence of Moments 7. Chebyshev’s Inequality 8. Further Inequalities. Convex Functions 9. Simple Conditional Distributions. Mixtures 10. Conditional Distributions 11. Conditional Expectations 12. Problems for Solution Chapter VI A Survey of Some Important Distributions and Processes 1. Stable Distributions in R1 2. Examples 3. Infinitely Divisible Distributions in R1 4. Processes with Independent Increments 5. Ruin Problems in Compound Poisson Processes 6. Renewal Processes 7. Examples and Problems 8. Random Walks 9. The Queuing Process 10. Persistent and Transient Random Walks 11. General Markov Chains 12. Martingales 13. Problems for Solution Chapter VII Laws of Large Numbers. Applications in Analysis 1. Main Lemma and Notations 2. Bernstein Polynomials. Absolutely Monotone Functions 3. Moment Problems 4. Application to Exchangeable Variables 5. Generalized Taylor Formula and Semi-Groups 6. Inversion Formulas for Laplace Transforms 7. Laws of Large Numbers for Identically Distributed Variables 8. Strong Laws 9. Generalization to Martingales 10. Problems for Solution Chapter VIII The Basic Limit Theorems 1. Convergence of Measures 2. Special Properties 3. Distributions as Operators 4. The Central Limit Theorem 5. Infinite Convolutions 6. Selection Theorems 7. Ergodic Theorems for Markov Chains 8. Regular Variation 9. Asymptotic Properties of Regularly Varying Functions 10. Problems for Solution Chapter IX Infinitely Divisible Distributions and Semi-Groups 1. Orientation 2. Convolution Semi-Groups 3. Preparatory Lemmas 4. Finite Variances 5. The Main Theorems 6. Example: Stable Semi-Groups 7. Triangular Arrays with Identical Distributions 8. Domains of Attraction 9. Variable Distributions. The Three-Series Theorem 10. Problems for Solution Chapter X Markov Processes and Semi-Groups 1. The Pseudo-Poisson Type 2. A Variant: Linear Increments 3. Jump Processes 4. Diffusion Processes in R1 5. The Forward Equation. Boundary Conditions 6. Diffusion in Higher Dimensions 7. Subordinated Processes 8. Markov Processes and Semi-Groups 9. The "Exponential Formula" of Semi-Group Theory 10. Generators. The Backward Equation Chapter XI Renewal Theory 1. The Renewal Theorem 2. Proof of the Renewal Theorem 3. Refinements 4. Persistent Renewal Processes 5. The Number Nt of Renewal Epochs 6. Terminating (Transient) Processes 7. Diverse Applications 8. Existence of Limits in Stochastic Processes 9. Renewal Theory on the Whole Line 10. Problems for Solution Chapter XII Random Walks in R1 1. Basic Concepts and Notations 2. Duality. Types of Random Walks 3. Distribution of Ladder Heights. Wiener-Hopf Factorization 3a. The Wiener-Hopf Integral Equation 4. Examples 5. Applications 6. A Combinatorial Lemma 7. Distribution of Ladder Epochs 8. The Arc Sine Laws 9. Miscellaneous Complements 10. Problems for Solution Chapter XIII Laplace Transforms. Tauberian Theorems. Resolvents 1. Definitions. The Continuity Theorem 2. Elementary Properties 3. Examples 4. Completely Monotone Functions. Inversion Formulas 5. Tauberian Theorems 6. Stable Distributions 7. Infinitely Divisible Distributions 8. Higher Dimensions 9. Laplace Transforms for Semi-Groups 10. The Hille-Yosida Theorem 11. Problems for Solution Chapter XIV Applications of Laplace Transforms 1. The Renewal Equation: Theory 2. Renewal-Type Equations: Examples 3. Limit Theorems Involving Arc Sine Distributions 4. Busy Periods and Related Branching Processes 5. Diffusion Processes 6. Birth-and-Death Processes and Random Walks 7. The Kolmogorov Differential Equations 8. Example: The Pure Birth Process 9. Calculation of Ergodic Limits and of First-Passage Times 10. Problems for Solution Chapter XV Characteristic Functions 1. Definition. Basic Properties 2. Special Distributions. Mixtures 2a. Some Unexpected Phenomena 3. Uniqueness. Inversion Formulas 4. Regularity Properties 5. The Central Limit Theorem for Equal Components 6. The Lindeberg Conditions 7. Characteristic Functions in Higher Dimensions 8. Two Characterizations of the Normal Distribution 9. Problems for Solution Chapter XVI Expansions Related to the Central Limit Theorem, 1. Notations 2. Expansions for Densities 3. Smoothing 4. Expansions for Distributions 5. The Berry-Esséen Theorems 6. Expansions in the Case of Varying Components 7. Large Deviations Chapter XVII Infinitely Divisible Distributions 1. Infinitely Divisible Distributions 2. Canonical Forms. The Main Limit Theorem 2a. Derivatives of Characteristic Functions 3. Examples and Special Properties 4. Special Properties 5. Stable Distributions and Their Domains of Attraction 6. Stable Densities 7. Triangular Arrays 8. The Class L 9. Partial Attraction. "Universal Laws" 10. Infinite Convolutions 11. Higher Dimensions 12. Problems for Solution 595 Chapter XVIII Applications of Fourier Methods to Random Walks 1. The Basic Identity 2. Finite Intervals. Wald’s Approximation 3. The Wiener-Hopf Factorization 4. Implications and Applications 5. Two Deeper Theorems 6. Criteria for Persistency 7. Problems for Solution Chapter XIX Harmonic Analysis 1. The Parseval Relation 2. Positive Definite Functions 3. Stationary Processes 4. Fourier Series 5. The Poisson Summation Formula 6. Positive Definite Sequences 7. L2 Theory 8. Stochastic Processes and Integrals 9. Problems for Solution Answers to Problems Some Books on Cognate Subjects Index

Read more less

Book SynopsisA unique introduction to the innovative methodology of statistical flowgraphs This book offers a practical, application-based approach to flowgraph models for time-to-event data. It clearly shows how this innovative new methodology can be used to analyze data from semi-Markov processes without prior knowledge of stochastic processes--opening the door to interesting applications in survival analysis and reliability as well as stochastic processes. Unlike other books on multistate time-to-event data, this work emphasizes reliability and not just biostatistics, illustrating each method with medical and engineering examples. It demonstrates how flowgraphs bring together applied probability techniques and combine them with data analysis and statistical methods to answer questions of practical interest. Bayesian methods of data analysis are emphasized. Coverage includes: * Clear instructions on how to model multistate time-to-event data using flowgraph models * An empTrade Review"…this is a well-written book on a novel and interesting approach to multistate modeling." (Biometrics, September 2006) "This book is one that researchers interested in techniques for multistate models, either in reliability or biometry should look at." (Journal of the American Statistical Association, September 2006) "…a real addition to the toolbox of both biostatisticians who use survival analysis and reliability engineers who do failure analysis on a regular basis." (Technometrics, February 2006) “…illustrated with interesting examples…the book is particularly welcome…” (International Statistical Institute, January 2006) "...a useful...account of the use of flowgraphy or semi-Markov parametric models in both industrial and biological applications." (Journal of Biopharmaceutical Statistics, September/October 2005) "Methods are explained comprehensively, with extensive examples…data analysts would find valuable examples here for their own applications." (Computing Reviews.com, June 2, 2005) “Fruitful medical and engineering examples and applications are presented…” (Zentralblatt Math, Vol.1055, No.06, 2005)Table of ContentsPreface. 1. Multistate Models and Flowgraph Models. 2. Flowgraph Models. 3. Inversion of Flowgraph Moment Generating Functions. 4. Censored Data Histograms. 5. Bayesian Prediction for Flowgraph Models. 6. Computation Implementation of Flowgraph Models. 7. Semi-Markov Processes. 8. Incomplete Data. 9. Flowgraph Models for Queuing Systems. Appendix: Moment Generating Functions. References. Author Index. Subject Index.

Read more less

Book SynopsisThis book is written from the perspective of a physicist, not a mathematician, with an emphasis on modern practical applications in the physical and engineering sciences. The book itself is essentially software, written in the language of Mathematica, the widely used and highly praised Mathematica software package.Trade Review"...a very valuable addition to the literature of the field..." (Zentralblatt Math, Vol. 1029, 2004) "...offers a comprehensive Mathematica-based guide to the analytical and numerical methods used every day...includes many exercises and worked examples..." (The Mathematica Journal, Vol. 9 No. 1)Table of ContentsPreface. Ordinary Differential Equations in the Physical Sciences. Fourier Series and Transforms. Introduction to Linear Partial Differential Equations. Eigenmode Analysis. Partial Differential Equations in Infinite Domains. Numerical Solution of Linear Partial Differential Equations. Nonlinear Partial Differential Equations. Introduction to Random Processes. An Introduction to Mathematica (Electronic Version Only). Appendix: Finite-Differenced Derivatives. Index.

Read more less

Book SynopsisThe smart student''s secret to study success The Student Solutions Manual to accompany Calculus: Ideas and Applications helps students ensure their own success. With fully-worked solutions to every odd-numbered problem in the text, this book allows students to gauge their understanding, avoid incorrect habits, and study smarter instead of longer. Having immediate feedback on independent work helps students spot their own mistakes, and the ability to check their work against the correct process can reveal hidden issues with concepts, calculations, arithmetic, and more.

Read more less

Book SynopsisLeslie Kish formulated, among other things, the 'margin of error,' an assessment of the accuracy of opinion polls. He was elected president of the American Statistical Association; and at once a remarkable teacher, thinker, and leader in the field of survey statistics. This volume collects Kish's most important papers.Trade Review“…bringing together a lifetime of research and practice, this volume is both a fitting tribute…and a highly useful…compilation of insight into the art and science of survey statistics…” (Zentralbaltt MATH, June 2005) “...collects, for the first time, the most important and influential papers by Leslie Kish...the editors have been immensely successful in bringing out this volume which will find a place on the bookshelf of every serious reader in the field.” (Mathematical Reviews, 2004c)Table of ContentsForeword—Dr. Xavier Charoy, President IASS. Preface—Rhea Kish. ROLE OF PROBABILITY SAMPLING IN SCIENTIFIC RESEARCH. The Hundred Years' Wars of Survey Sampling (1995). Some Statistical Problems in Research Design (1959). APPLIED SAMPLING METHODS. A Procedure for Objective Respondent Selection Within the Household (1949). Controlled Selection—A Technique in Probability Sampling (1950). Sampling Organizations and Groups of Unequal Sizes (1965). Retaining Units After Changing Strata and Probabilities (1971). Multivariate and Multipurpose Stratification (1978). ISSUES IN INFERENCE FROM SURVEY DATA. Inference From Complex Samples (1974). Methods for Design Effects (1995). Weighting for Unequal Pi (1992). NONSAMPLING ERRORS. Response Errors in Estimating the Value of Homes (1954). Studies of Interviewer Variance for Attitudinal Variables (1962). DOMAIN ESTIMATION. Multipurpose Sample Designs. Postcensal Estimates for Local Areas (or Domains) (1980). Cum ulating/Combining Population Surveys (1999). PROFESSIONAL LEADERSHIP AND TRAINING. Chance, Statistics and Statisticians (1978). Developing Samplers for Developing Countries (1996). References. Index.

Read more less

Book SynopsisDescribes various analytical techniques and systems for the development, validation, quality control, purification, and physicochemical testing of combinatorial libraries. This book provides coverage of applications of Nuclear Magnetic Resonance (NMR), liquid chromatography/mass spectrometry (LC/MS), and Fourier Transform Infrared (FTIR).Trade Review"…a timely and valuable volume that would be an excellent addition to university libraries and the collections of individuals…" (E-STREAMS, February 2005) "...a useful book for chemists entering the field from either analytical or synthetic organic chemistry backgrounds.” (Angewandte Chemie International Edition, September 6, 2004) "This useful volume is a worthwhile addition to institute libraries as well as to the libraries students and researchers who are working in analytical chemistry, medicinal chemistry, organic chemistry, biotechnology…" (Energy Sources, August 2004)Table of ContentsPreface. Contributors. PART I: ANALYSIS FOR FEASIBILITY AND OPTIMIZATION OF LIBRARY SYNTHESIS. Chapter 1. Quantitative Analysis in Organic Synthesis with NMR (L. Lucas & C. Larive). Chapter 2. 19F Gel-phase NMR Spectroscopy for Reaction Monitoring and Quantification of Resin Loading (J. Salvino). Chapter 3. The Application of Single-Bead FTIR and Color Test for Reaction Monitoring and Building Block Validation in Combinatorial Library Sysnthesis(J. Cournoyer, et al.). Chapter 4. HR-MAS NMR Analysis of Compounds Attached to Polymer Supports (M. Guinó & Y. de Miguel). Chapter 5. Multivariate Tools for Real-Time Monitoring and Optimization of Combinatorial Materials and Process Conditions (R. Potyrailo, et al.). Chapter 6. Mass Spectrometry and Soluble Polymeric Supports (C. Enjalbal, et al.). PART II: HIGH-THROUGHPUT ANALYSIS FOR LIBRARY QUALITY CONTROL. Chapter 7. High-Throughput NMR Techniques for Combinatorial Chemical Library Analysis (T. Hou & D. Raftery). Chapter 8. Micellar Electrokinetic Chromatography as a Tool for Combinatorial Chemistry Analysis: Theory and Applications (P. Simms). Chapter 9. Characterization of Split-Pool Encoded Combinatorial Libraries (J. Zhang & W. Fitch). PART III: HIGH-THROUGHPUT PURIFICATION TO IMPROVE LIBRARY QUALITY. Cha pter 10. Strategies and Methods for Purifying Organic Compounds and Combinatorial Libraries (J. Zhao, et al.). Chapter 11. HTP of Combinatorial Chemistry Libraries (J. Hochlowski). Chapter 12. Practical HPLC in High Throughput Analysis and Purification (H. Gumm & R. God). PART IV: ANALYSIS FOR COMPOUND STABILITY AND DRUGABILITY. Chapter 13. Organic Compound Stability in Large, Diverse Phatmaceutical Screening Collection (K. Morand & X. Cheng). Chapter 14. Quartz Crystal Microbalance in Biomolecular Recognition (M. Tseng, et al.). Chapter 15. High-Throughput Physicochemical Profiling: Potential and Limitations (B. Faller). Chapter 16. Solubility in the Design of Combinatorial Libraries (C. Lipinski). Chapter 17. High-Throughput Determination of Log D Values by LC/MS Method (J. Villena, et al.). Index.

Read more less

Book SynopsisCALCULUS + PEPPERONI / FUN = MATH SUCCESS Do you want to do well on your calculus exam? Are you looking for a quick refresher course? Or would you just like to get a taste of what calculus is all about? If so, you've selected the right book.Table of ContentsPreface. Acknowledgments. Introduction. Pizza Velocity and the Derivative. Derivative Definitions and Rules. Derivatives and and Slopes. Rules for Products and Quotients. Chain Rule and Implicit Differentiation. Maxima and Minima. Min-Max Pizza Applications. Exponentials and Logarithms. Limits and Continuity. Related Rates. Integration. Logarithmic Differentiation, Integration by Parts, Trigonometric Substitution, and Partial Fractions. Exponential Growth and Decay. Calculus and Computers. Multiple Integrals. Calculus in a Nutshell. Luigi's Mind-Boggling Workout Routine. Conclusion. Answers. Further Reading. Index.

Read more less

Book SynopsisThis Set Contains: Continuous Multivariate Distributions, Volume 1, Models and Applications, 2nd Edition by Samuel Kotz, N. Balakrishnan and Normal L. Johnson Continuous Univariate Distributions, Volume 1, 2nd Edition by Samuel Kotz, N. Balakrishnan and Normal L. Johnson Continuous Univariate Distributions, Volume 2, 2nd Edition by Samuel Kotz, N. Balakrishnan and Normal L. Johnson Discrete Multivariate Distributions by Samuel Kotz, N. Balakrishnan and Normal L. Johnson Univariate Discrete Distributions, 3rd Edition by Samuel Kotz, N. Balakrishnan and Normal L. Johnson Discover the latest advances in discrete distributions theory The Third Edition of the critically acclaimed Univariate Discrete Distributions provides a self-contained, systematic treatment of the theory, derivation, and application of probability distributions for count data. Generalized zeta-function and q-series distributTrade Review“With its thorough coverage and balanced presentation of theory and application, this is an excellent and essential reference for statisticians and mathematicians.” (Xolosepo, 27 October 2012) "The authors continue to do a praise-worthy job of making the material accessible in the third edition. This book should be on every library's shelf." (Journal of the American Statistical Association, September 2006) "These authors have achieved considerable renown for their comprehensive books on statistical distributions." (Technometrics, August 2006) "Encyclopedic in nature, the book continues to be a valuable reference." (Mathematical Reviews, 2006d) "This is an important book that should be part of every statistician's library." (MAA Reviews, January 2, 2006)Table of ContentsPreface xvii 1 Preliminary Information 1 1.1 Mathematical Preliminaries 1 1.1.1 Factorial and Combinatorial Conventions 1 1.1.2 Gamma and Beta Functions 5 1.1.3 Finite Difference Calculus 10 1.1.4 Differential Calculus 14 1.1.5 Incomplete Gamma and Beta Functions and Other Gamma-Related Functions 16 1.1.6 Gaussian Hypergeometric Functions 20 1.1.7 Confluent Hypergeometric Functions (Kummer’s Functions) 23 1.1.8 Generalized Hypergeometric Functions 26 1.1.9 Bernoulli and Euler Numbers and Polynomials 29 1.1.10 Integral Transforms 32 1.1.11 Orthogonal Polynomials 32 1.1.12 Basic Hypergeometric Series 34 1.2 Probability and Statistical Preliminaries 37 1.2.1 Calculus of Probabilities 37 1.2.2 Bayes’s Theorem 41 1.2.3 Random Variables 43 1.2.4 Survival Concepts 45 1.2.5 Expected Values 47 1.2.6 Inequalities 49 1.2.7 Moments and Moment Generating Functions 50 1.2.8 Cumulants and Cumulant Generating Functions 54 1.2.9 Joint Moments and Cumulants 56 1.2.10 Characteristic Functions 57 1.2.11 Probability Generating Functions 58 1.2.12 Order Statistics 61 1.2.13 Truncation and Censoring 62 1.2.14 Mixture Distributions 64 1.2.15 Variance of a Function 65 1.2.16 Estimation 66 1.2.17 General Comments on the Computer Generation of Discrete Random Variables 71 1.2.18 Computer Software 73 2 Families of Discrete Distributions 74 2.1 Lattice Distributions 74 2.2 Power Series Distributions 75 2.2.1 Generalized Power Series Distributions 75 2.2.2 Modified Power Series Distributions 79 2.3 Difference-Equation Systems 82 2.3.1 Katz and Extended Katz Families 82 2.3.2 Sundt and Jewell Family 85 2.3.3 Ord’s Family 87 2.4 Kemp Families 89 2.4.1 Generalized Hypergeometric Probability Distributions 89 2.4.2 Generalized Hypergeometric Factorial Moment Distributions 96 2.5 Distributions Based on Lagrangian Expansions 99 2.6 Gould and Abel Distributions 101 2.7 Factorial Series Distributions 103 2.8 Distributions of Order-k 105 2.9 q-Series Distributions 106 3 Binomial Distribution 108 3.1 Definition 108 3.2 Historical Remarks and Genesis 109 3.3 Moments 109 3.4 Properties 112 3.5 Order Statistics 116 3.6 Approximations, Bounds, and Transformations 116 3.6.1 Approximations 116 3.6.2 Bounds 122 3.6.3 Transformations 123 3.7 Computation, Tables, and Computer Generation 124 3.7.1 Computation and Tables 124 3.7.2 Computer Generation 125 3.8 Estimation 126 3.8.1 Model Selection 126 3.8.2 Point Estimation 126 3.8.3 Confidence Intervals 130 3.8.4 Model Verification 133 3.9 Characterizations 134 3.10 Applications 135 3.11 Truncated Binomial Distributions 137 3.12 Other Related Distributions 140 3.12.1 Limiting Forms 140 3.12.2 Sums and Differences of Binomial-Type Variables 140 3.12.3 Poissonian Binomial, Lexian, and Coolidge Schemes 144 3.12.4 Weighted Binomial Distributions 149 3.12.5 Chain Binomial Models 151 3.12.6 Correlated Binomial Variables 151 4 Poisson Distribution 156 4.1 Definition 156 4.2 Historical Remarks and Genesis 156 4.2.1 Genesis 156 4.2.2 Poissonian Approximations 160 4.3 Moments 161 4.4 Properties 163 4.5 Approximations, Bounds, and Transformations 167 4.6 Computation, Tables, and Computer Generation 170 4.6.1 Computation and Tables 170 4.6.2 Computer Generation 171 4.7 Estimation 173 4.7.1 Model Selection 173 4.7.2 Point Estimation 174 4.7.3 Confidence Intervals 176 4.7.4 Model Verification 178 4.8 Characterizations 179 4.9 Applications 186 4.10 Truncated and Misrecorded Poisson Distributions 188 4.10.1 Left Truncation 188 4.10.2 Right Truncation and Double Truncation 191 4.10.3 Misrecorded Poisson Distributions 193 4.11 Poisson–Stopped Sum Distributions 195 4.12 Other Related Distributions 196 4.12.1 Normal Distribution 196 4.12.2 Gamma Distribution 196 4.12.3 Sums and Differences of Poisson Variates 197 4.12.4 Hyper-Poisson Distributions 199 4.12.5 Grouped Poisson Distributions 202 4.12.6 Heine and Euler Distributions 205 4.12.7 Intervened Poisson Distributions 205 5 Negative Binomial Distribution 208 5.1 Definition 208 5.2 Geometric Distribution 210 5.3 Historical Remarks and Genesis of Negative Binomial Distribution 212 5.4 Moments 215 5.5 Properties 217 5.6 Approximations and Transformations 218 5.7 Computation and Tables 220 5.8 Estimation 222 5.8.1 Model Selection 222 5.8.2 P Unknown 222 5.8.3 Both Parameters Unknown 223 5.8.4 Data Sets with a Common Parameter 226 5.8.5 Recent Developments 227 5.9 Characterizations 228 5.9.1 Geometric Distribution 228 5.9.2 Negative Binomial Distribution 231 5.10 Applications 232 5.11 Truncated Negative Binomial Distributions 233 5.12 Related Distributions 236 5.12.1 Limiting Forms 236 5.12.2 Extended Negative Binomial Model 237 5.12.3 Lagrangian Generalized Negative Binomial Distribution 239 5.12.4 Weighted Negative Binomial Distributions 240 5.12.5 Convolutions Involving Negative Binomial Variates 241 5.12.6 Pascal–Poisson Distribution 243 5.12.7 Minimum (Riff–Shuffle) and Maximum Negative Binomial Distributions 244 5.12.8 Condensed Negative Binomial Distributions 246 5.12.9 Other Related Distributions 247 6 Hypergeometric Distributions 251 6.1 Definition 251 6.2 Historical Remarks and Genesis 252 6.2.1 Classical Hypergeometric Distribution 252 6.2.2 Beta–Binomial Distribution, Negative (Inverse) Hypergeometric Distribution: Hypergeometric Waiting-Time Distribution 253 6.2.3 Beta–Negative Binomial Distribution: Beta–Pascal Distribution, Generalized Waring Distribution 256 6.2.4 Pólya Distributions 258 6.2.5 Hypergeometric Distributions in General 259 6.3 Moments 262 6.4 Properties 265 6.5 Approximations and Bounds 268 6.6 Tables Computation and Computer Generation 271 6.7 Estimation 272 6.7.1 Classical Hypergeometric Distribution 273 6.7.2 Negative (Inverse) Hypergeometric Distribution: Beta–Binomial Distribution 274 6.7.3 Beta–Pascal Distribution 276 6.8 Characterizations 277 6.9 Applications 279 6.9.1 Classical Hypergeometric Distribution 279 6.9.2 Negative (Inverse) Hypergeometric Distribution: Beta–Binomial Distribution 281 6.9.3 Beta–Negative Binomial Distribution: Beta–Pascal Distribution, Generalized Waring Distribution 283 6.10 Special Cases 283 6.10.1 Discrete Rectangular Distribution 283 6.10.2 Distribution of Leads in Coin Tossing 286 6.10.3 Yule Distribution 287 6.10.4 Waring Distribution 289 6.10.5 Narayana Distribution 291 6.11 Related Distributions 293 6.11.1 Extended Hypergeometric Distributions 293 6.11.2 Generalized Hypergeometric Probability Distributions 296 6.11.3 Generalized Hypergeometric Factorial Moment Distributions 298 6.11.4 Other Related Distributions 299 7 Logarithmic and Lagrangian Distributions 302 7.1 Logarithmic Distribution 302 7.1.1 Definition 302 7.1.2 Historical Remarks and Genesis 303 7.1.3 Moments 305 7.1.4 Properties 307 7.1.5 Approximations and Bounds 309 7.1.6 Computation, Tables, and Computer Generation 310 7.1.7 Estimation 311 7.1.8 Characterizations 315 7.1.9 Applications 316 7.1.10 Truncated and Modified Logarithmic Distributions 317 7.1.11 Generalizations of the Logarithmic Distribution 319 7.1.12 Other Related Distributions 321 7.2 Lagrangian Distributions 325 7.2.1 Otter’s Multiplicative Process 326 7.2.2 Borel Distribution 328 7.2.3 Consul Distribution 329 7.2.4 Geeta Distribution 330 7.2.5 General Lagrangian Distributions of the First Kind 331 7.2.6 Lagrangian Poisson Distribution 336 7.2.7 Lagrangian Negative Binomial Distribution 340 7.2.8 Lagrangian Logarithmic Distribution 341 7.2.9 Lagrangian Distributions of the Second Kind 342 8 Mixture Distributions 343 8.1 Basic Ideas 343 8.1.1 Introduction 343 8.1.2 Finite Mixtures 344 8.1.3 Varying Parameters 345 8.1.4 Bayesian Interpretation 347 8.2 Finite Mixtures of Discrete Distributions 347 8.2.1 Parameters of Finite Mixtures 347 8.2.2 Parameter Estimation 349 8.2.3 Zero-Modified and Hurdle Distributions 351 8.2.4 Examples of Zero-Modified Distributions 353 8.2.5 Finite Poisson Mixtures 357 8.2.6 Finite Binomial Mixtures 358 8.2.7 Other Finite Mixtures of Discrete Distributions 359 8.3 Continuous and Countable Mixtures of Discrete Distributions 360 8.3.1 Properties of General Mixed Distributions 360 8.3.2 Properties of Mixed Poisson Distributions 362 8.3.3 Examples of Poisson Mixtures 365 8.3.4 Mixtures of Binomial Distributions 373 8.3.5 Examples of Binomial Mixtures 374 8.3.6 Other Continuous and Countable Mixtures of Discrete Distributions 376 8.4 Gamma and Beta Mixing Distributions 378 9 Stopped-Sum Distributions 381 9.1 Generalized and Generalizing Distributions 381 9.2 Damage Processes 386 9.3 Poisson–Stopped Sum (Multiple Poisson) Distributions 388 9.4 Hermite Distribution 394 9.5 Poisson–Binomial Distribution 400 9.6 Neyman Type A Distribution 403 9.6.1 Definition 403 9.6.2 Moment Properties 405 9.6.3 Tables and Approximations 406 9.6.4 Estimation 407 9.6.5 Applications 409 9.7 Pólya–Aeppli Distribution 410 9.8 Generalized Pólya–Aeppli (Poisson–Negative Binomial) Distribution 414 9.9 Generalizations of Neyman Type A Distribution 416 9.10 Thomas Distribution 421 9.11 Borel–Tanner Distribution: Lagrangian Poisson Distribution 423 9.12 Other Poisson–Stopped Sum (multiple Poisson) Distributions 425 9.13 Other Families of Stopped-Sum Distributions 426 10 Matching, Occupancy, Runs, and q-Series Distributions 430 10.1 Introduction 430 10.2 Probabilities of Combined Events 431 10.3 Matching Distributions 434 10.4 Occupancy Distributions 439 10.4.1 Classical Occupancy and Coupon Collecting 439 10.4.2 Maxwell–Boltzmann, Bose–Einstein, and Fermi–Dirac Statistics 444 10.4.3 Specified Occupancy and Grassia–Binomial Distributions 446 10.5 Record Value Distributions 448 10.6 Runs Distributions 450 10.6.1 Runs of Like Elements 450 10.6.2 Runs Up and Down 453 10.7 Distributions of Order k 454 10.7.1 Early Work on Success Runs Distributions 454 10.7.2 Geometric Distribution of Order k 456 10.7.3 Negative Binomial Distributions of Order k 458 10.7.4 Poisson and Logarithmic Distributions of Order k 459 10.7.5 Binomial Distributions of Order k 461 10.7.6 Further Distributions of Order k 463 10.8 q-Series Distributions 464 10.8.1 Terminating Distributions 465 10.8.2 q-Series Distributions with Infinite Support 470 10.8.3 Bilateral q-Series Distributions 474 10.8.4 q-Series Related Distributions 476 11 Parametric Regression Models and Miscellanea 478 11.1 Parametric Regression Models 478 11.1.1 Introduction 478 11.1.2 Tweedie–Poisson Family 480 11.1.3 Negative Binomial Regression Models 482 11.1.4 Poisson Lognormal Model 483 11.1.5 Poisson–Inverse Gaussian (Sichel) Model 484 11.1.6 Poisson Polynomial Distribution 487 11.1.7 Weighted Poisson Distributions 488 11.1.8 Double-Poisson and Double-Binomial Distributions 489 11.1.9 Simplex–Binomial Mixture Model 490 11.2 Miscellaneous Discrete Distributions 491 11.2.1 Dandekar’s Modified Binomial and Poisson Models 491 11.2.2 Digamma and Trigamma Distributions 492 11.2.3 Discrete Adès Distribution 494 11.2.4 Discrete Bessel Distribution 495 11.2.5 Discrete Mittag–Leffler Distribution 496 11.2.6 Discrete Student’s t Distribution 498 11.2.7 Feller–Arley and Gegenbauer Distributions 499 11.2.8 Gram–Charlier Type B Distributions 501 11.2.9 “Interrupted” Distributions 502 11.2.10 Lost-Games Distributions 503 11.2.11 Luria–Delbrück Distribution 505 11.2.12 Naor’s Distribution 507 11.2.13 Partial-Sums Distributions 508 11.2.14 Queueing Theory Distributions 512 11.2.15 Reliability and Survival Distributions 514 11.2.16 Skellam–Haldane Gene Frequency Distribution 519 11.2.17 Steyn’s Two-Parameter Power Series Distributions 521 11.2.18 Univariate Multinomial-Type Distributions 522 11.2.19 Urn Models with Stochastic Replacements 524 11.2.20 Zipf-Related Distributions 526 11.2.21 Haight’s Zeta Distributions 533 Bibliography 535 Abbreviations 631 Index 633

Read more less

Book SynopsisIf you're an engineer or scientist who has suddenly been thrust into the world of management, you may find yourself thinking that managing people is more of a challenge than your former highly technical job. Veteran management consultant Michael K. Badawy couldn't agree more. He says, The primary problems of engineering and R&D management are not technicalthey are human. Badawy offers real help for the human side of technical management in his classic Developing Managerial Skills in Engineers and Scientists. Since 1982, thousands of technical executives, supervisors, managers, and students have turned to this classic for hands-on management techniques. This thoroughly revised second edition hones in on issues facing today's technical manager: Total Quality Management Technological entrepreneurship Cross-functional teams Success requirement for project management Interdepartmental interfacing Educating technologists in managing techTable of ContentsTHE PRACTICE OF TECHNICAL MANAGEMENT. Technical Management in Action. Preventing Managerial Failure. TRANSFORMATION OF TECHNOLOGISTS INTO MANAGERS. Issues in Career Transition. TECHNOLOGIES FOR CAREER TRANSITION. Technologies for Management. Technologies for Engineers and Scientists. Educating Technologists for Management. THE ORGANIZING FUNCTION. Fundamental Principles Every Technical Manager Should Know. Managing Without Authority--Project, Matrix, and Cross-Functional Teams. Developing Your Organizational Design Skills. THE PLANNING AND DECISION-MAKING FUNCTION. Understanding Managerial and Strategic Planning. Developing Your Decision-Making and Problem-Solving Skills. THE CONTROLLING AND EVALUATION FUNCTION. Developing Your Control and Evaluation Skills. Measuring and Evaluating Engineering and R&D. LOOKING AHEAD. The Quest for Quality: Managers Beware. Index.

Read more less

Book SynopsisA complete and balanced account of communication theory, providing an understanding of both Fourier analysis (and the concepts associated with linear systems) and the characterization of such systems by mathematical operators. Presents applications of the theories to the diffraction of optical wave-fields and the analysis of image-forming systems.Table of ContentsRepresentation of Physical Quantities by MathematicalFunctions. Special Functions. Harmonic Analysis. Mathematical Operators and Physical Systems. Convolution. The Fourier Transform. Characteristics and Applications of Linear Filters. Two-Dimensional Convolution and Fourier Transformation. The Propagation and Diffraction of Optical Wave Fields. Image-Forming Systems. Appendices. Index.

Read more less

Book SynopsisComplete coverage of the prediction approach to survey sampling in a single resource Prediction theory has been extremely influential in survey sampling for nearly three decades, yet research findings on this model-based approach are scattered in disparate areas of the statistical literature.Trade Review"Valliant...is joined...to dispel the perception of dichotomy between mainstream statistics...and survey sampling..." (SciTech Book News, Vol. 24, No. 4, December 2000) "The vast majority of the book is devoted to prediction of a population mean or total, and as such it forms a cohesive and comprehensive treatment of the subject." (Mathematical Reviews, Issue 2001j) "A highly recommended book which is an essential read for all research workers in this area." (Short Book Reviews - Publication of the Int. Statistical Institute, December 2001) "This book is a welcome addition to the subject of survey sampling." (Zentralblatt MATH, Vol. 964, 2001/14)Table of ContentsIntroduction to Prediction Theory. Prediction Theory Under the General Linear Model. Bias-Robustness. Robustness and Efficiency. Variance Estimation. Stratified Populations. Models with Qualitative Auxiliaries. Clustered Populations. Robust Variance Estimation in Two-Stage Cluster Sampling. Alternative Variance Estimation Methods. Special Topics and Open Questions. Appendices. Bibliography. Answers to Select Exercises. Indexes.

Read more less

Book SynopsisThe use of analytical methods in studies concerning works of art and archaeological artifacts provides essential information on the materials they are made from, including their composition, age, and methods used in their production. This book explains how to use analytical methods to obtain such information.Trade Review"Scientists...explain how analytical methods are being used tostudy works of art and archaeological artifacts...they discussbasic principles, procedures, and applications." (Reference &Research Book News, November 2001)Table of ContentsAnalytical Methods in Art and Archaeology (E. Ciliberto). Elemental Analysis (R. Hancock). Atomic Spectroscopy and Spectrometry (S. Young & A.Pollard). X-Ray Fluorescence (L. Moens, et al.). Neutron Activation Analysis for Provenance Determination inArchaeology (H. Neff). Particle-Induced X-Ray Emission (J.-C. Dran, et al.). Molecular and Structural Analysis (G. Spoto). Biomolecular Analysis by Organic Mass Spectrometry (R.Evershed). Biomolecular Methods (R. Cano). Raman Spectroscopy (F. Cariati & S. Bruni). Thermal Analysis (M. Odlyha). UV-VIS-NIR, FT-IR, AND FORS Spectroscopies (M. Bacci). X-Ray Photoelectron Spectroscopy and Auger Electron Spectroscopy inArt An Archaeology (G. Spoto & E. Ciliberto). Electron Microscopy and its Application to the Study ofArchaeological Materials and Art Preservation (M. Jose-Yacaman& J. Ascencio). Isotope Analysis, Dating, and Provenance Methods (G. Wagner). Radiocarbon Dating (R. Hedges). Lead Isotope Analyses Applied to Provenance Studies (N. Gale &Z. Stos-Gale). Luminescence Dating (S. Troja & R. Roberts). Electron Spin Resonance Dating (R. Grun). Data Handling and Statistical Analysis (M. Baxter & C.Buck). Index.

Read more less

Book SynopsisThis edition continues to provide analytical chemists and statisticians with the latest practical information on using statistical tools in chemical data analysis. The accompanying FTP site contains a series of programs that illustrate the statistical techniques which are discussed in the book.Trade Review“This new edition of a successful, bestselling book continues to provide you with practical information on the useof statistical methods for solving real-world problems in complex industrial environments.” (PDFCHM Online, 27 February 2013) "...a comprehensive, very useful and clear guide for all analytical chemists..." (Annali di Chimica, Vol 153, 2000) "Substantially updated...for lab supervisors and project mangers, and is useful...for advanced students of chemistry and pharmaceutical science." (SciTech Book News, Vol. 24, No. 2, June 2001) "Its clarity, focus and logical approach to statistical analysis of chemical data make it a book that should appear on the bookshelf of most analytical chemists." (Journal of the American Chemical Society, Vol. 123 No. 36)Table of ContentsUnivariate Data. Bi- and Multivariate Data. Related Topics. Complex Examples. Appendices. Technical Tidbits. Glossary. References. Index.

Read more less

Book SynopsisA posteriori error estimators have been intensely studied in recent years, owing to their remarkable capacity to enhance both speed and accuracy in computing. By effectively estimating error, the door has been opened for the possibility of controlling the entire computational process through new adaptive algorithms.Table of ContentsPreface xiii Acknowledgments xvii 1 Introduction 1 1.1 A Posteriori Error Estimation: The Setting 1 1.2 Status and Scope 2 1.3 Finite Element Nomenclature 4 1.3.1 Sobolev Spaces 5 1.3.2 Inverse Estimates 7 1.3.3 Finite Element Partitions 9 1.3.4 Finite Element Spaces on Triangles 10 1.3.5 Finite Element Spaces on Quadrilaterals 11 1.3.6 Properties of Lagrange Basis Functions 12 1.3.7 Finite Element Interpolation 12 1.3.8 Patches of Elements 13 1.3.9 Regularized Approximation Operators 14 1.4 Model Problem 15 1.5 Properties of A Posteriori Error Estimators 16 1.6 Bibliographical Remarks 18 2 Explicit A Posteriori Estimators 19 2.1 Introduction 19 2.2 A Simple A Posteriori Error Estimate 20 2.3 Efficiency of Estimator 23 2.3.1 Bubble Functions 23 2.3.2 Bounds on the Residuals 28 2.3.3 Proof of Two-Sided Bounds on the Error 31 2.4 A Simple Explicit Least Squares Error Estimator 32 2.5 Estimates for the Pointwise Error 34 2.5.1 Regularized Point Load 35 2.5.2 Regularized Green's Function 38 2.5.3 Two-Sided Bounds on the Pointwise Error 39 2.6 Bibliographical Remarks 4% 3 Implicit A Posteriori Estimators 43 3.1 Introduction 43 3.2 The Subdomain Residual Method 44 3.2.1 Formulation of Subdomain Residual Problem 45 3.2.2 Preliminaries 46 3.2.3 Equivalence of Estimator ^7 3.2.4 Treatment of Residual Problems 49 3.3 The Element Residual Method 50 3.3.1 Formulation of Local Residual Problem 50 3.3.2 Solvability of the Local Problems 52 3.3.3 The Classical Element Residual Method 54 3.3.4 Relationship with Explicit Error Estimators 54 3.3.5 Efficiency and Reliability of the Estimator 55 3.4 The Influence and Selection of Subspaces 56 3.4.1 Exact Solution of Element Residual Problem 56 3.4.2 Analysis and Selection of Approximate Subspaces 59 3.4.3 Conclusions 62 3.5 Bibliographical Remarks 63 4 Recovery-Based Error Estimators 65 4.1 Examples of Recovery-Based Estimators 66 4.1.1 An Error Estimator for a Model Problem in One Dimension 61 4.1.2 An Error Estimator for Bilinear Finite Element Approximation 69 4.2 Recovery Operators 72 4.2.1 Approximation Properties of Recovery Operators 73 4.3 The Superconvergence Property 75 4.4 Application to A Posteriori Error Estimation 76 4.5 Construction of Recovery Operators 77 4.6 The Zienkiewicz-Zhu Patch Recovery Technique 79 4.6.1 Linear Approximation on Triangular Elements 79 4.6.2 Quadratic Approximation on Triangular Elements 81 4.6.3 Patch Recovery for Quadrilateral Elements 82 4.7 A Cautionary Tale 82 4.8 Bibliographical Remarks 83 5 Estimators, Indicators, and Hierarchic Bases 85 5.1 Introduction 85 5.2 Saturation Assumption 88 5.3 Analysis of Estimator 89 5.4 Error Estimation Using a Reduced Subspace 90 5.5 The Strengthened Cauchy-Schwarz Inequality 94 5.6 Examples 98 5.7 Multilevel Error Indicators 100 5.8 Bibliographical Remarks 109 6 The Equilibrated Residual Method 111 6.1 Introduction 111 6.2 The Equilibrated Residual Method 112 6.3 The Equilibrated Flux Conditions 116 6.4 Equilibrated Fluxes on Regular Partitions 117 6.4.1 First-Order Equilibration Condition 118 6.4.2 The Form of the Boundary Fluxes 118 6.4.3 Equilibration Conditions in Terms of the Moments 120 6.4.4 Local Patch Problems for the Flux Moments 120 6.4.5 Procedure for Resolution of Patch Problems 123 6.4.6 Summary 127 6.5 Efficiency of the Estimator 128 6.5.1 Stability of the Equilibrated Fluxes 128 6.5.2 Proof of Efficiency of the Estimator 131 6.6 Equilibrated Fluxes on Partitions Containing Hanging Nodes 133 6.6.1 First-Order Equilibration 133 6.6.2 Flux Moments for Unconstrained Nodes 134 6.6.3 Flux Moments with Respect to Constrained Nodes 137 6.6.4 Recovery of Actual Fluxes 137 6.7 Equilibrated Fluxes for Higher-Order Elements 139 6.7.1 The Form of the Boundary Fluxes 141 6.7.2 Determination of the Flux Moments 141 6.8 Bibliographical Remarks 143 7 Methodology for the Comparison of Estimators 145 7.1 Introduction 145 7.2 Overview of the Technique 146 7.3 Approximation over an Interior Subdomain 149 7.3.1 Translation Invariant Meshes 149 7.3.2 Lower Bounds on the Error 152 7.3.3 Interior Estimates 153 7.4 Asymptotic Finite Element Approximation 157 7.4.1 Periodic Finite Element Projection on Reference Cell 157 7.4.2 Periodic Finite Element Projection on a Physical Cell 158 7.4.3 Periodic Extension on a Subdomain 159 7.4.4 Asymptotic Finite Element Approximation 160 7.5 Stability of Estimators 165 7.5.1 Verification of Stability Condition for Explicit Estimator 166 7.5.2 Verification of Stability Condition for Implicit Estimators 168 7.5.3 Verification of Stability Condition for Recovery-Based Estimator 169 7.5.4 Elementary Consequences of the Stability Condition 170 7.5.5 Evaluation of Effectivity Index in the Asymptotic Limit 172 7.6 An Application of the Theory 174 7.6.1 Computation of Asymptotic Finite Element Solution 174 7.6.2 Evaluation of the Error in Asymptotic Finite Element Approximation 178 7.6.3 Computation of Limits on the Asymptotic Effectivity Index for Zienkiewicz-Zhu Patch Recovery Estimator 180 7.6.4 Application to Equilibrated Residual Method 184 7.6.5 Application to Implicit Element Residual Method 184 7.7 Bibliographical Remarks 187 8 Estimation of the Errors in Quantities of Interest 189 8.1 Introduction 189 8.2 Estimates for the Error in Quantities of Interest 191 8.3 Upper and Lower Bounds on the Errors 193 8.4 Goal-Oriented Adaptive Refinement 197 8.5 Example of Goal-Oriented Adaptivity 198 8.5.1 Adaptivity Based on Control of Global Error in Energy 198 8.5.2 Goal-Oriented Adaptivity Based on Pointwise Quantities of Interest 198 8.6 Local and Pollution Errors 202 8.7 Bibliographical Remarks 205 9 Some Extensions 207 9.1 Introduction 207 9.2 Stokes and Oseen's Equations 208 9.2.1 A Posteriori Error Analysis 211 9.2.2 Summary 218 9.3 Incompressible Navier-Stokes Equations 219 9.4 Extensions to Nonlinear Problems 222 9.4.1 A Class of Nonlinear Problems 222 9.4.2 A Posteriori Error Estimation 224 9.4.3 Estimation of the Residual 225 9.5 Bibliographical Remarks 227 References 229 Index 239

Read more less

Book SynopsisA powerful new way to navigate today's unprecedented market conditions "Bill Williams' pioneering application of chaos theory to the financial markets is leading technical analysis into the twenty-first century and beyond.Table of ContentsBlasting Off. From Chaos to Cosmos to Cash. The Alligator. The Fractal-The Breakaway Trade. The Awesome Oscillator. The Market Accelerator. Trading in the Zones. The Balance Line Trades. Techniques for Taking Profits. Tying It All Together. How to Become a Master Trader. Bibliography. About the Author. Index.

Read more less

Book SynopsisFourier Series and Optical Transform Techniques in ContemporaryOptics An Introduction For anyone new to Fourier methods, this remarkable book willilluminate the subject like no other currently available. With over280 illustrations generated by computer graphics, it depicts in3-space (rather than the usual 2-space) the many basic functions ofoptical diffraction and imaging. These mind-stretchingvisualizations give the reader an enhanced understanding of bothFourier transform techniques and key principles in optics. At thesame time, the author provides a lucid text that covers wavenotation, the Fourier analysis of signals, the processing of lightin diffraction phenomena and imaging, Zernicke polynomials, Fouriertransforms for Fresnel diffraction, laser beacon adaptive optics,and related topics. Ideal for self-teaching, this book is highly recommended forworking engineers, technical staff, students of physical optics andsignal analysis, and Fourier novices in alTable of ContentsPartial table of contents: Some of the How and Why of Fourier Analysis. Fourier Series and Spectra in One-Dimension for Functions of FinitePeriod. Fourier Series and Spectra for Functions of Infinite Period; One Dimensional. Fourier Spectra for Non-Periodic Functions; One-Dimensional. The Diffraction of Light and Fourier Transforms in TwoDimensions. A Brief Summary of Linear Systems Theory Applied to OpticalImaging. Fourier Optical Transformations by Computer. Apodization and Super-Resolution, Phase from Shift, and MultipleApertures. Complex Apertures. Operations in the Fourier Transform Plane. Other Interesting and Related Topics. References. A Selected Bibliography. Index.

Read more less

Book SynopsisWith the growing complexity of engineered systems, reliability has increased in importance throughout the twentieth century. Initially developed to meet practical needs, reliability theory has become an applied mathematical discipline that permits a priori evaluations of various reliability indices at the design stages.Table of ContentsFundamentals. Reliability Indexes. Unrepairable Systems. Load-Strength Reliability Models. Distributions with Monotone Intensity Functions. Repairable Systems. Repairable Duplicated Systems. Analysis of Performance Effectiveness. Two-Pole Networks. Optimal Redundancy. Optimal Technical Diagnosis. Additional Optimization Problems in Reliability Theory. Heuristic Methods in Reliability. Index.

Read more less

Book SynopsisReinforcing concepts with frequent exercises and extended applications, this introduction to the theoretical and computational aspects of linear algebra uses the MATLAB software to master the basic algorithms and to increase the speed and efficiency of computations.Table of ContentsMatrix Algebra. Vector Spaces and Linear Transformations. Orthogonality and Projections. Eigenvalues and Eigenvectors. The Spectral Theorem and Applications. Normal Forms. Appendices. Bibliography. Index.

Read more less

Book SynopsisA general purpose work on sampling method and theory. Volume 1 gives a simple, non-mathematical discussion of principles and their practical applications. Volume 2 covers theory and proofs.Table of ContentsFUNDAMENTAL THEORY. Operations, Events and Probability. Random Variables, Expected Values, Variances, Covariances, andConvergence in Probability. DERIVATIONS, PROOFS, AND SOME EXTENSIONS OF THEORY FORCORRESPONDING CHAPTERS OF VOLUME 1. Simple Random Sampling. Stratified Simple Random Sampling. Simple One- or More Stage Cluster Sampling. Stratified Single- or Multi-Stage Cluster Sampling. Control of Variation in Size of Cluster in Estimating Totals,Averages, or Ratios. Multi-Stage Sampling with Large Primary Sampling Units. Estimating Variances. Regression Estimates, Double Sampling, Sampling for Time Series,and Other Sampling Methods. A THEORY FOR RESPONSE ERRIRS. Response Errors in Surveys. Index.

Read more less

Book SynopsisA general purpose work on sampling method and theory. Volume 1 gives a simple, non-mathematical discussion of principles and their practical applications. Volume 2 covers theory and proofs.Table of ContentsAn Elementary Survey of Sampling Principles. Biases and Nonsampling Errors in Survey Results. Sample Designs for Some Common Sampling Problems. Simple Random Sampling. Stratified Random Sampling. Simple One- or Two-Stage Cluster Sampling. Stratified Single or Multi-Stage Cluster Sampling. Control of Variation in Size of Cluster in Estimating Totals,Averages, or Ratios. Multi-Stage Sampling with Large Primary Sampling Units. Estimating Variances. Regression Estimates, Double Sampling, Sampling for Time Series,Systematic Sampling, and Other Sampling Methods. Case Studies--Designs and Results of Some Actual SampleSurveys. Appendix. Index.

Read more less

Book SynopsisThis book focuses on when to use the various analytic techniques and how to interpret the resulting output from the most widely used statistical packages (e.g. , SAS, SPSS).Table of ContentsGeometric Concepts of Data Manipulation. Fundamentals of Data Manipulation. Principal Components Analysis. Factor Analysis. Confirmatory Factor Analysis. Cluster Analysis. Two-Group Discriminant Analysis. Multiple-Group Discriminant Analysis. Logistic Regression. Multivariate Analysis of Variance. Assumptions. Canonical Correlation. Covariance Structure Models. Statistical Tables. References. Tables, Figures, and Exhibits. Index.

Read more less

Book SynopsisExperts from the world''s major financial institutions contributed to this work and have already used the newest technologies. Gives proven strategies for using neural networks, algorithms, fuzzy logic and nonlinear data analysis techniques to enhance profitability. The latest analytical breakthroughs, the impact on modern finance theory and practice, including the best ways for profitably applying them to any trading and portfolio management system, are all covered.Table of ContentsPartial table of contents: TRADING WITH NEURAL NETWORKS. Neural Network Techniques (C. Klimasauskas). Adaptive Selection of U.S. Stocks with Neural Nets (J. Hall). Intelligent Trading of an Emerging Market (G.-S. Jang & F. Lai). Neural Nets for Foreign Exchange Trading (H. Green & M.Pearson). STRATEGY OPTIMIZATION WITH GENETIC ALGORITHMS. Genetic Algorithms for Financial Modeling (A. Colin). PORTFOLIO MANAGEMENT USING FUZZY LOGIC. Why Use Fuzzy Modeling? (G. Deboeck). Smart Trading with FRET (D. Benachenhou). NONLINEAR DYNAMICS AND CHAOS. Nonlinear Data Analysis Techniques (T. Frison). RISK MANAGEMENT AND THE IMPACT OF TECHNOLOGY. The Cutting Edge of Trading Technology (G. Deboeck). Glossary. Bibliography. Index.

Read more less

Book SynopsisThe subject of operator algebras has experienced tremendous growth in recent years with significant applications to areas within algebraic mathematics as well as allied areas such as single operator theory, non-self-adjoint operator algegras, K-theory, knot theory, ergodic theory, and mathematical physics. This book makes recent developments in operator algebras accessible to the non-specialist.Table of ContentsFundamentals. Spectrum and Order. Examples and Constructions. Von Neumann Algebras. Representations. Structure Theory. Tensor Products. Crossed Products. Factors. K-Theory. References. Index.

Read more less

Book SynopsisCritical Acclaim for Pi and the AGM: "Fortunately we have the Borwein's beautiful book... explores in the first five chapters the glorious world so dear to Ramanujan... would be a marvelous text book for a graduate course.Table of ContentsComplete Elliptic Integrals and the Arithmetic-Geometric MeanIteration. Theta Functions and the Arithmetic-Geometric Mean Iteration. Jacobi's Triple-Product and Some Number TheoreticApplications. Higher Order Transformations. Modular Equations and Algebraic Approximations to pi. The Complexity of Algebraic Functions. Algorithms for the Elementary Functions. General Means and Iterations. Some Additional Applications. Other Approaches to the Elementary Functions. Pi. Bibliography. Symbol List. Index.

Read more less

Book SynopsisIncludes proof of van der Waerden''s 1926 conjecture on permanents, Wilson''s theorem on asymptotic existence, and other developments in combinatorics since 1967. Also covers coding theory and its important connection with designs, problems of enumeration, and partition. Presents fundamentals in addition to latest advances, with illustrative problems at the end of each chapter. Enlarged appendixes include a longer list of block designs.Table of ContentsPermutations and Combinations. Inversion Formulae. Generating Functions and Recursions. Partitions. Distinct Representatives. Ramsey's Theorem. Some Extremal Problems. Convex Spaces and Linear Programming. Graphical Methods, Debruijn Sequences. Block Designs. Difference Sets. Finite Geometries. Orthogonal Latin Squares. Hadamard Matrices. General Constructions of Block Designs. Theorems on Completion and Embedding. Coding Theory and Block Designs. Appendices. Bibliography. Index.

Read more less

Book SynopsisRegression analysis is the study of the dependence of a response variable on one or more predictor variables. It is among the most widely used methods in statistics. In recent years, several new ways to approach regression have been presented.Trade Review"...with its up-to-date discussion of regression graphics at a very accessible level, Applied Regression Including Computing and Graphics is a must for everyone working in the area of regression analysis. I strongly recommend it as a text..." (Journal of the American Statistical Association, September 2001) "...a must for everyone working in the area of regression analysis. I strongly recommend it as a text..." (Journal of the American Statistical Association, September 2001)Table of ContentsLooking Forward and Back. Introduction to Regression. Introduction to Smoothing. Bivariate Distributions. Two-Dimensional Plots. TOOLS. Simple Linear Regression. Introduction to Multiple Linear Regression. Three-Dimensional Plots. Weights and Lack-of-Fit. Understanding Coefficients. Relating Mean Functions. Factors and Interactions. Response Transformations. Diagnostics I: Curvature and Nonconstant Variance. Diagnostics II: Influence and Outliers. Predictor Transformations. Model Assessment. REGRESSION GRAPHICS. Visualizing Regression. Visualizing Regression with Many Predictors. Graphical Regression. LOGISTIC REGRESSION AND GENERALIZED LINEAR MODELS. Binomial Regression. Graphical and Diagnostic Methods for Logistic Regression. Generalized Linear Models. Appendix. References. Indexes.

Read more less

Book SynopsisThis text is a coherent account of the science of decision making. It includes the models of operations research and those models of probability that relate to decision making. An emphasis in placed between these connections and relates these models to nearly all of the professions.Table of ContentsPreface. PART A: INTRODUCTION. The Science of Decision Making. Getting Started with Spreadsheets. PART B: USING LINEAR PROGRAMS. Analyzing Solutions of Linear Programs. A Survey of Linear Programs. Networks. Integer Programs. PART C: PROBABILITY FOR DECISION MAKING. Introduction to Probability Models. Discrete Random Variables. Decision Trees and Generalizations. Utility Theory and Decision Analysis. Continuous Random Variables. PART D: STOCHASTIC SYSTEMS. Inventory. Markov Chains. Queueing. Simulation. PART E: GAME THEORY. Game Theory. PART F: SOLVING LINEAR PROGRAMS. Solving Linear Equations. The Simplex Method. Duality. Appendix: Note on Excel. Index.

Read more less

Book SynopsisThis book introduces the reader to the fundamental principles, definitions, and results of dynamical systems and chaos. Rather than relegating chaos to the last chapter in the book, as is usually the case, this work treats chaos as an integral part of dynamical systems theory.Trade Review"From the preface: 'The purpose of this book is to present the fundamental ideas on discrete dynamical systems and chaos at the level of those undergraduates...who have completed the standard calculus sequence, with the inclusion of functions of several variables and linear algebra.'" (Mathematical Reviews, Issue 2001k)Table of ContentsDiscrete Dynamical Systems. One-Dimensional Dynamical Systems. R¯q, Matrices, and Functions. Discrete Linear Dynamical Systems. Nonlinear Dynamical Systems. Chaotic Behavior. Analysis of Four Dynamical Systems. Appendices. Index.

Read more less

Book SynopsisThis volume describes the algebra of matrices and shows how to apply them to today's problems in applied economics. The first section covers the essentials of matrices while the second section concentrates on major topics in applied economics such as regression, linear programming, and time series.Trade Review"Suitable for a graduate level course on matrix for statisticsstudents. The book is written in an applied style and students willlike it." (Journal of Statistical Computation andSimulation, March 2006) "...well suited to its purpose...content is beautifully laidout..." (Mathematics Today, June 2004) "...designed for students of economics and for practicingeconomists..." (Quarterly of Applied Mathematics, Vol. LX,No. 1, March 2002) "Textbook suitable for a one-semester course introduces matrixalgebra and its application to economic problems." (Journal ofEconomic Literature, Vol. 40, No. 1, March 2002) "A textbook...explaining to students of economics how matrixalgebra is used in the profession...No prior mathematics is assumedbeyond high school algebra..." (Reference & Research BookNews, May 2002) "...practising economists who want to gain more mathematicalskills will also find the book at the right level..."(Zentralblatt Math, Vol. 982, No. 07, 2002) "...an excellent introductory text..." (Journal of theAmerican Statistical Association, December 1, 2002)Table of ContentsList of Chapters. Preface. BASICS. Introduction. Basic Matrix Operations. Special Matrices. Determinants. Inverse Matrices. NECESSARY THEORY. Linearly (IN)Dependent Vectors. Rank. Canonical Forms. Generalized Inverses. Solving Linear Equations. Eigenroots and Eigenvectors. Miscellanea. WORKING WITH MATRICES. Applying Linear Equations. Regression Analysis. Linear Statistical Models. Linear Programming. Markov Chain Models. References. Index.

Read more less

Book SynopsisThis title develops introductory topics in probability and statistics with particular emphasis on concepts that arise in computer science. It starts with the basic definitions of probability distributions and random variables and elaborates their properties and applications.Trade Review"This text will fill a gap in the education of a sophisticated computer science student who has a firm base in mathematics and statistics." (Computing Reviews, May 7, 2009) "…this textbook would be ideal." (The American Statistician, February 2006) "This is really a statistics textbook written explicitly for undergraduate computer science majors…I found the numerous examples of the use of statistics within the field of computer science extremely informative." (Technometrics, November 2004) "Thorough, in-depth, relatively complete and rigorous introduction to the statistics a CS professional should know." (American Mathematical Monthly, August 2004) "This is a rigorous introductory text in probability and statistics, which also develops in a rigorous fashion all the necessary supporting mathematics beyond calculus and algebra." (Mathematical Reviews, issue 2004i) "...one-of-a-kind resource...proves an ideal resource for computer science students and practitioners interested in a probability study..." (Zentralblatt Math, Vol. 1027, 2004) “...presents introductory topics in probability and statistics with particular emphasis on concepts that arise in computer science...disguised also by the feature that it develops all necessary supporting mathematics in a thorough and rigorous fashion.” (Quarterly of Applied Mathematics, Vol. LXI, No. 4, December 2003)Table of ContentsPreface. 1. Combinatorics and Probability. 2. Discrete Distributions. 3. Simulation. 4. Discrete Decision Theory. 5. Real Line-Probability. 6. Continuous Distributions. 7. Parameter Estimation. Appendix A. Analytical Tools. Appendix B. Statistical Tables. Bibliography. Index.

Read more less

Book SynopsisThis text provides lively reading, with compelling applications, projects, and experiments that supply readers with opportunities to explore the relationship between the parameters in a differential equation and the process it models. Its goal is to teach readers to use differential equation as an investigative tool, not just to verify results.Table of ContentsBasic Concepts. Autonomous Differential Equations. First Order Differential Equations - Qualitative and Quantitative Aspects. Models and Applications Leading to New Techniques. First Order Linear Differential Equations and Models. Interplay Between First Order Systems and Second OrderEquations. Second Order Linear Differential Equations with ForcingFunctions. Second Order Linear Differential Equations - Qualitative and Quantitative Aspects. Linear Autonomous Systems. Nonlinear Autonomous Systems. Using Laplace Transforms. Using Power Series. Appendices. Answers. Index.

Read more less

Book SynopsisThis text combines lucid and statistically engaging exposition, graphic and applied examples, and realistic exercise settings, to take students past the mechanics of introductory-level statistical techniques into the realm of practical data analysis, and inference-based problem solving.Trade Review"...a superb book....Wild & Seber have now raised the standard of introductory textbooks another notch." (Australian & New Zealand, 2000)Table of ContentsWhat Is Statistics? Tools for Exploring Univariate Data. Exploratory Tools for Relationships. Probabilities and Proportions. Discrete Random Variables. Continuous Random Variables. Sampling Distributions of Estimates. Confidence Intervals. Significance Testing: Using Data to Test Hypotheses. Data on a Continuous Variable. Tables of Counts. Relationships between Quantitative Variables: Regression and Correlation. Control Charts. Time Series. Appendices. References. Answers to Selected Problems. Index.

Read more less

Book SynopsisUnderstanding how to properly manage urban stormwater is a critical concern to civil and environmental engineers the world over. Mismanagement of stormwater and urban runoff results in flooding, erosion, and water quality problems.Table of ContentsURBAN STORMWATER MANAGEMENT. Urban Drainage Systems: Evolution of Problems. Urban Runoff Quantity and Quality Control Strategies. Urban Stormwater Management Modeling. DATA ANALYSIS. Meteorological Data Analysis. Runoff Quality Data Analysis. DRAINAGE SYSTEM PERFORMANCE ANALYSIS. Elements of Derived Probability Distribution Theory. Model of Urban Drainage System. Quantity Control Analysis of Urban Drainage Systems. Advanced Quantity Control Analysis. Multiple Reservoir Systems. Quality Control Analysis of Urban Drainage Systems. Urban Drainage Systems Analysis: Optimization and SensitivityAnalysis. Appendices. Glossary. Notation. Index.

Read more less

Book SynopsisThis work aims to offer an accessible introduction to the theory of complex analysis - a fundamental branch of mathematics that has important applications in many areas of the physical sciences. It introduces the connection to problem states in terms of real analysis.Trade Review"...well written ,very readable...stylish, up-to-date text..." (The Mathematical Gazette, July 2002) McGehee discusses the basics of complex variables and a few applications to physics in a rigorous and understandable manner. He begins with motivation and the necessary background of the subject in chapter 1. Chapter 2 includes the fundamentals of the algebra, geometry, and calculus of complex numbers. The core topics (Cauchy's theorem and the residue calculus) of complex variable make up chapters 3 and 4. The author then applies the techniques of complex variables to various boundary value problems in chapter 5. A few of the more mathematically challenging results and their proofs are discussed in Chapter 6. McGehee includes more than 520 exercises (many with hints), nearly 100 detailed examples, and Mathematical-generated illustrations on approximately 20 percent of the pages. These features enable readers to deepen their geometric, computational, and theoretical understanding of the material. Upper-division undergraduates through professionals. (CHOICE, April 2001, Vol. 38, No. 8) A versatile textbook offering all the material, at an appropriate level of treatment, for a first course...in complex analysis but also containing some more avanced material in the final chapter. A useful feature is that each chapter ends with not only a selection of exercises but also a "Hints on selected exercises" section. (Aslib Book Guide, May 2001, Vol 66, No 5) "...sophisticated approach that stresses the geometry of complex mappings." (Journal of Natural Products American Mathematical Monthly, November 2001) "...gives a solid introduction to function theory...emphasized by many pictures that help the student a lot to understand better they underlying concepts." (Zentralblatt MATH, Vol. 970, 2001/20) "...deserves to join the list of classic texts that precede it..." (SIAM Review, Vol. 44, No. 1, March 2002) "...stylish, up-to-date text...a very welcome addition to the literature." (The Mathematical Gazette, Vol. 86, No. 506, 2002)Table of ContentsPreliminaries. Basic Tools. The Cauchy Theory. The Residue Calculus. Boundary Value Problems. Lagniappe. References. Index.

Read more less