Probability and statistics Books
Cambridge University Press B Nard Cells and Taylor Vortices
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£122.55
Cambridge University Press Forecasting Structural Time Series Models and the Kalman Filter
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£36.09
Cambridge University Press LMS 162 Harmonic Analysis Theory London Mathematical Society Lecture Note Series Series Number 162
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£50.95
Cambridge University Press stochasticanalysisproceedingsofthedurhamsymposiumonstochasticanalysis
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£74.13
Cambridge University Press Applied Nonparametric Regression
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£36.87
Cambridge University Press Scaling Selfsimilarity and Intermediate Asymptotics Dimensional Analysis and Intermediate Asymptotics 14 Cambridge Texts in Applied Mathematics Series Number 14
Book SynopsisScaling laws reveal the fundamental property of phenomena, namely self-similarity - repeating in time and/or space - which substantially simplifies the mathematical modelling of the phenomena themselves. This book begins from a non-traditional exposition of dimensional analysis, physical similarity theory, and general theory of scaling phenomena, using classical examples to demonstrate that the onset of scaling is not until the influence of initial and/or boundary conditions has disappeared but when the system is still far from equilibrium. Numerous examples from a diverse range of fields, including theoretical biology, fracture mechanics, atmospheric and oceanic phenomena, and flame propagation, are presented for which the ideas of scaling, intermediate asymptotics, self-similarity, and renormalisation were of decisive value in modelling.Trade Review'A splendid and very readable work … Greatly recommended!' Sjoerd Rienstra, ITW NieuwsTable of ContentsPreface; Introduction; 1. Dimensions, dimensional analysis and similarity; 2. The application of dimensional analysis to the construction of intermediate asymptotic solutions to problems of mathematical physics. Self-similar solutions; 3. Self-similarities of the second kind: first examples; 4. Self-similarities of the second kind: further examples; 5. Classification of similarity rules and self-similarity solutions. Recipe for application of similarity analysis; 6. Scaling and transformation groups. Renormalization groups. 7. Self-similar solutions and travelling waves; 8. Invariant solutions: special problems of the theory; 9. Scaling in deformation and fracture in solids; 10. Scaling in turbulence; 11. Scaling in geophysical fluid dynamics; 12. Scaling: miscellaneous special problems.
£72.19
Cambridge University Press Spectral Analysis for Physical Applications Multitaper and Conventional Univariate Techniques
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£82.64
Cambridge University Press Numerical Recipes in Fortran Example Book The Art Of Scientific Computing
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£40.84
Cambridge University Press Random Graphs 53 Encyclopedia of Mathematics and its Applications Series Number 53
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£95.95
Cambridge University Press Acta Numerica 1993 Volume 2 Acta Numerica Series Number 2
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£85.50
Cambridge University Press Creating Modern Probability
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£76.94
Cambridge University Press Neural Networks and Qualitative Physics
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£114.95
Cambridge University Press Observing Interaction
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£95.00
Cambridge University Press Combinatorial Methods in Discrete Mathematics 55 Encyclopedia of Mathematics and its Applications Series Number 55
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£105.45
Cambridge University Press LMS 194 Independnt Random Variable London Mathematical Society Lecture Note Series Series Number 194
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£45.16
Cambridge University Press Some Random Series Functions 2ed 5 Cambridge Studies in Advanced Mathematics Series Number 5
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£66.49
Cambridge University Press Statistical Analysis Spherical Data
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£75.99
Cambridge University Press Sampling and Statistical Methods for Behavioral Ecologists
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£40.84
Cambridge University Press Complexity Knots Colourings and Countings 186 London Mathematical Society Lecture Note Series Series Number 186
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£57.57
Cambridge University Press Topics in the Constructive Theory of Countable Markov Chains
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£104.50
Cambridge University Press Statistical Methods in Biology
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£42.74
Cambridge University Press Complexity and Information
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£42.74
Cambridge University Press Geometric Scattering Theory
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£82.64
Cambridge University Press Generalised EulerJacobi Inversion Formula and Asymptotics beyond All Orders 214 London Mathematical Society Lecture Note Series Series Number 214
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£47.63
Cambridge University Press Geometric Scattering Theory 1 Stanford Lectures Distinguished Visiting Lecturers in Mathematics Series Number 1
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£33.24
Cambridge University Press Uniform Central Limit Theorems 142 Cambridge Studies in Advanced Mathematics Series Number 142
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£84.55
Cambridge University Press Bayesian Nonparametrics 28 Cambridge Series in Statistical and Probabilistic Mathematics Series Number 28
Book SynopsisBayesian nonparametrics works. Applications are appearing in such disciplines as information retrieval, NLP, machine vision, computational biology, cognitive science, signal processing. In this coherent introduction, the editors weave together tutorial chapters by Ghosal, Lijoi and Prünster, Dunson, and Teh and Jordan, giving direct access to these exciting ideas and methods.Trade Review"The book looks like it will be useful to a wide range of researchers. I like that there is a lot of discussion of the models themselves as well as the computation. The book, especially in the early chapters, is more theoretical than I would prefer... But, hey, that's just my taste... on the whole I think the book is excellent. If I didn't think the book was important, I wouldn't be spending my time pointing out my disagreements with it!" Andrew Gelman, Columbia University"The book provides a tour de force presentation of selected topics in an emerging branch of modern statistical science, and not only justfies the reader’s curiosity, but also expands it.... The book brings together a well-structured account of a number of topics on the theory, methodology, applications, and challenges of future developments in the rapidly expanding area of Bayesian nonparametrics. Given the current dearth of books on BNP, this book will be an invaluable source of information and reference for anyone interested in BNP, be it a student, an established statistician, or a researcher in need of flexible statistical analyses." Milovan Krnjajic, Journal of the American Statistical AssociationTable of ContentsAn invitation to Bayesian nonparametrics Nils Lid Hjort, Chris Holmes, Peter Müller and Stephen G. Walker; 1. Bayesian nonparametric methods: motivation and ideas Stephen G. Walker; 2. The Dirichlet process, related priors, and posterior asymptotics Subhashis Ghosal; 3. Models beyond the Dirichlet process Antonio Lijoi and Igor Prünster; 4. Further models and applications Nils Lid Hjort; 5. Hierarchical Bayesian nonparametric models with applications Yee Whye Teh and Michael I. Jordan; 6. Computational issues arising in Bayesian nonparametric hierarchical models Jim Griffin and Chris Holmes; 7. Nonparametric Bayes applications to biostatistics David B. Dunson; 8. More nonparametric Bayesian models for biostatistics Peter Müller and Fernando Quintana; Author index; Subject index.
£72.19
Cambridge University Press Stochastic Approximation
Book SynopsisSimple, compact toolkit for designing and analyzing algorithms, with concrete examples from control and communications engineering, artificial intelligence, economic modelling.Trade Review'I highly recommend [this book] to all readers interested in the theory of recursive algorithms and its applications in practice.' Mathematical Reviews'This simple compact toolkit for designing and analyzing stochastic approximation algorithms requires only basic literacy in probability and differential equations … Ideal for graduate students, researchers and practitioners in electrical engineering and computer science, especially those working in control, communications, signal processing and machine learning, this book is also relevant to economics, probability and statistics.' L'Enseignement MathématiqueTable of ContentsPreface; 1. Introduction; 2. Basic convergence analysis; 3. Stability criteria; 4. Lock-in probability; 5. Stochastic recursive inclusions; 6. Multiple timescales; 7. Asynchronous schemes; 8. A limit theorem for fluctuations; 9. Constant stepsize algorithms; 10. Applications; 11. Appendices; References; Index.
£55.09
Cambridge University Press Theory of Decision under Uncertainty 45 Econometric Society Monographs
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£78.85
Cambridge University Press Time Series Analysis and Inverse Theory for Geophysicists
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£59.84
Cambridge University Press Nonlinear Time Series Analysis
Book SynopsisThe paradigm of deterministic chaos has influenced thinking in many fields of science. Chaotic systems show rich and surprising mathematical structures. In the applied sciences, deterministic chaos provides a striking explanation for irregular behaviour and anomalies in systems which do not seem to be inherently stochastic. The most direct link between chaos theory and the real world is the analysis of time series from real systems in terms of nonlinear dynamics. Experimental technique and data analysis have seen such dramatic progress that, by now, most fundamental properties of nonlinear dynamical systems have been observed in the laboratory. Great efforts are being made to exploit ideas from chaos theory wherever the data displays more structure than can be captured by traditional methods. Problems of this kind are typical in biology and physiology but also in geophysics, economics, and many other sciences.Trade ReviewFrom reviews of the first edition: '… any serious physics institute should have such a book on its shelves. It will be of use to any experimental scientist dealing with nonlinear data or a theoretical physicist who desires a feeling of 'how one does it in an experiment'. The clear course of presentation should make it accessible to undergraduate students.' Daniel Wojcik, Pageoph'This book will be of value to any graduate student or researcher who needs to be able to analyse time series data, especially in the fields of physics, chemistry, biology, geophysics, medicine, economics and the social sciences.' Mathematical Reviews'… a very readable introduction to the concepts and clear descriptions of the techniques, as well as cautions, where appropriate, about potential pitfalls and misuses of the methods. … the book is a good reference to the current state of the art from the nonlinear dynamics community and is important reading for anyone faced with interpreting irregular time series.' Contemporary PhysicsTable of ContentsPreface; Acknowledgements; Part I. Basic Topics: 1. Introduction: why nonlinear methods?; 2. Linear tools and general considerations; 3. Phase space methods; 4. Determinism and predictability; 5. Instability: Lyapunov exponents; 6. Self-similarity: dimensions; 7. Using nonlinear methods when determinism is weak; 8. Selected nonlinear phenomena; Part II. Advanced Topics: 9. Advanced embedding methods; 10. Chaotic data and noise; 11. More about invariant quantities; 12. Modelling and forecasting; 13. Non-stationary signals; 14. Coupling and synchronisation of nonlinear systems; 15. Chaos control; Appendix A: using the TISEAN programs; Appendix B: description of the experimental data sets; References; Index.
£71.24
Cambridge University Press Elementary Probability
Book SynopsisNow available in a fully revised and updated second edition, this well established textbook provides a straightforward introduction to the theory of probability. The presentation is entertaining without any sacrifice of rigour; important notions are covered with the clarity that the subject demands. Topics covered include conditional probability, independence, discrete and continuous random variables, basic combinatorics, generating functions and limit theorems, and an introduction to Markov chains. The text is accessible to undergraduate students and provides numerous worked examples and exercises to help build the important skills necessary for problem solving.Trade Review'… this book is a superb resource of theory and application, which should be on every lecturer's shelves, and those of many students. You may never need to buy another book on probability.' Keith Hirst, The Mathematical Gazette'Excellent! A vast number of well-chosen worked examples and exercises guide the reader through the basic theory of probability at the elementary level … an excellent text which I am sure will give a lot of pleasure to students and teachers alike.' International Statistics Institute'… would make a fine addition to an undergraduate library. A student with a solid background in calculus, linear algebra, and set theory will find many useful tools of elementary probability here.' Phil Gilbert, The Mathematics Teacher'Stirzaker does an excellent job of developing problem-solving skills in an introductory probability text. Numerous examples and practice exercises are provided that only serve to enhance a student's problem solving abilities … Highly recommended.' D. J. Gougeon, Choice'The book would make an excellent text for the properly prepared class, a solid instructor's reference for both probability applications and problems, as well as a fine work for purposes of self-study.' J. Philip Smith, School Science and Mathematics'This book is a valuable resource for anyone teaching probability-and, accordingly, I am glad to have it.' The Journal of the Royal Statistical Society'The strong feature of the textbook is a choice of good examples … the book is suitable for a first university course in probability and very useful for self-study.' EMS Newsletter'As the first edition, the book is very well written, in a clear, detailed and readable style. It is accessible for undergraduate students and would make a good textbook for first courses on probability or for self-study.' Zentralblatt MATHTable of Contents1. Probability; 2. Conditional probability and independence; 3. Counting; 4. Random variables: distribution and expectation; 5. Random vectors: independence and dependence; 6. Generating functions and their applications; 7. Continuous random variables; 8. Jointly continuous random variables; 9. Markov chains; Appendix.
£47.49
Cambridge University Press Longitudinal and Panel Data
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£44.64
Cambridge University Press Subjective Probability
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£28.99
Cambridge University Press Statistics
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£42.74
Cambridge University Press Structural Equation Modeling and Natural Systems
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£56.99
Cambridge University Press Multidimensional Real Analysis I
Book SynopsisPart one of the authors' comprehensive and innovative work on multidimensional real analysis. Numerous illustrative exercises combined with an exhaustive and transparent treatment of subject matter make the book ideal as either the text for a course, a source of problems for a seminar or for self study.Trade Review'Throughout the notation is carefully organized and all proofs are complete and rigorous. The text is completed by carefully worked examples, many of them are illustrated by drawings. A special feature of the book is the extensive collection of exercises … The book is a good preparation for readers who wish to go on to more advanced studies in analysis. It can be also highly recommended as a text for a course or for self study.' Zentralblatt fur MathematikTable of ContentsPreface; Acknowledgements; Introduction; 1. Continuity; 2. Differentiation; 3. Inverse function and implicit function theorems; 4. Manifolds; 5. Tangent spaces; Exercises; Notation; Index.
£91.19
Cambridge University Press Random Walks on Infinite Graphs and Groups
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£108.30
Cambridge University Press Lvy Processes and Infinitely Divisible Distributions 68 Cambridge Studies in Advanced Mathematics Series Number 68
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£128.25
Cambridge University Press Compliance Quantified
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£104.50
Cambridge University Press Gaussian Hilbert Spaces
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£131.10
Cambridge University Press The Econometric Analysis of Seasonal Time Series
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£89.87
Cambridge University Press The Econometric Analysis of Seasonal Time Series
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£37.99
Cambridge University Press Statistical Analysis of Circular Data
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£42.74
Cambridge University Press Mathematical Programs with Equilibrium Constraints
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£118.75
Cambridge University Press Observing Interaction
Book SynopsisThis book provides a straightforward introduction to scientific methods for observing social behavior. Because of the importance of time in the dynamics of social interaction, sequential approaches to analyzing and understanding social behavior are emphasized.Trade Review'The book is an excellent primer for the novice and a good methods reminder for the experienced. Its major point, that sequential observation has been ignored, is a good one. It is written in a clear, readable, self-contained style with the exception of the last two chapters which require the use of additional resources listed in the bibliography. It contains very useful tables and figures, examples, and repeated summaries of major points made in each chapter and chapter section.' American Journal of PrimatologyTable of ContentsPreface; 1. Introduction; 2. Developing a coding scheme; 3. Recording behavioral sequences; 4. Assessing observer agreement; 5. Representing observational data; 6. Analyzing sequential data: first steps; 7. Analyzing event sequences; 8. Issues in sequential analysis; 9. Analyzing time sequences; 10. Analyzing cross-classified events; 11. Epilogue; Appendix; References; Index.
£37.04
Cambridge University Press Numerical Recipes in Fortran 90 Volume 2 Volume 2 of Fortran Numerical Recipes The Art of Parallel Scientific Computing Fortran Numerical Recipes v 2
Book SynopsisNumerical Recipes in Fortran 90 starts with a detailed introduction to the Fortran 90 language and then presents the basic concepts of parallel programming. All 350+ routines from the second edition of Numerical Recipes are presented in Fortran 90. Many are completely reworked algorithmically so as to be 'parallel-ready' and to utilise Fortran 90's advanced language features. Numerical Recipes in Fortran 90 emphasises general principles, but throughout there are also numerous hints and tips. This volume is intended for use with the original Numerical Recipes in Fortran, 2nd Edition (now called Numerical Recipes in Fortran 77) and does not discuss how the individual programs are used, or how the mathematical methods are used. An excellent guide for Fortran programmers interested in moving to Fortran 90, or C/C++ programmers interested in parallel programming.Trade Review'This new edition begins with three completely new chapters that provide a detailed introduction to the Fortran 90 language and then present the basic concepts of parallel programming, all with the same clarity and good cheer for which Numerical Recipes is famous.' L'Enseignement Mathématique' … certainly recommendable'. Eric de Sturler, ITW NieuwsTable of Contents1. Introduction to Fortran 90 language features; 2. Introduction to parallel programming; 3. Numerical recipes utility functions for Fortran 90; Part I. Fortran 90 Code chapters: 4. Preliminaries; 5. Solution of linear algebraic equations; 6. Interpolation and extrapolation; 7. Integration of functions; 8. Evaluation of functions; 9. Special functions; 10. Random numbers; 11. Sorting; 12. Root finding and nonlinear sets of equations; 13. Minimization or maximization of functions; 14. Eigensystems; 15. Fast Fourier transform; 16. Fourier and spectral applications; 17. Statistical description of Data; 18. Modelling of data; 19. Integration of ordinary differential equations; 20. Two point boundary value problems; 21. Integral equations and inverse theory; 22. Partial differential equations; 23 Less-numerical algorithms; Part II. Appendices: 24. Listing of utility modules (nrtype and nrutil); 25. Listing of explicit interfaces; 26. Index of programs and dependencies.
£59.84
Cambridge University Press Estimation Inference and Specification Analysis
Book SynopsisThis book examines the consequences of misspecifications from the fundamental to the nonexistent for the interpretation of likelihood-based methods of statistical estimation and interference.Trade Review'... contains much material of interest to econometricians … a useful source book for researchers, instructors and graduate students and essential reading for those interested in the effects of misspecification.' Econometric TheoryTable of Contents1. Introductory remarks; 2. Probability densities, likelihood functions and the quasi-maximum likelihood estimator; 3. Consistency of the QMLE; 4. Correctly specified models of density; 5. Correctly specified models of conditional expectation; 6. The asymptotic distribution of the QMLE and the information matrix equality; 7. Asymptotic efficiency; 8. Hypothesis testing and asymptotic covariance matrix estimation; 9. Specification testing via m-tests; 10. Applications of m-testing; 11. Information matrix testing; 12. Conclusion; Appendix 1. Elementary concepts of measure theory and the Radon-Nikodym theorem; Appendix 2. Uniform laws of large numbers; Appendix 3. Central limit theorems.
£36.09