Probability and statistics Books
Springer Verlag, Singapore Statistical Inference Based on Kernel
Book SynopsisThis book presents a study of statistical inferences based on the kernel-type estimators of distribution functions. The inferences involve matters such as quantile estimation, nonparametric tests, and mean residual life expectation, to name just some. Convergence rates for the kernel estimators of density functions are slower than ordinary parametric estimators, which have root-n consistency. If the appropriate kernel function is used, the kernel estimators of the distribution functions recover the root-n consistency, and the inferences based on kernel distribution estimators have root-n consistency. Further, the kernel-type estimator produces smooth estimation results. The estimators based on the empirical distribution function have discrete distribution, and the normal approximation cannot be improved—that is, the validity of the Edgeworth expansion cannot be proved. If the support of the population density function is bounded, there is a boundary problem, namely the estimator does not have consistency near the boundary. The book also contains a study of the mean squared errors of the estimators and the Edgeworth expansion for quantile estimators.Table of Contents-1. Kernel density estimator-2. Kernel distribution estimator-3. Quantile estimation-4. Nonparametric tests-5. Mean residual life estimator
£999.99
Springer Verlag, Singapore Applied Linear Algebra, Probability and
Book SynopsisThis book focuses on research in linear algebra, statistics, matrices, graphs and their applications. Many chapters in the book feature new findings due to applications of matrix and graph methods. The book also discusses rediscoveries of the subject by using new methods. Dedicated to Prof. Calyampudi Radhakrishna Rao (C.R. Rao) who has completed 100 years of legendary life and continues to inspire us all and Prof. Arbind K. Lal who has sadly departed us too early, it has contributions from collaborators, students, colleagues and admirers of Professors Rao and Lal. With many chapters on generalized inverses, matrix analysis, matrices and graphs, applied probability and statistics, and the history of ancient mathematics, this book offers a diverse array of mathematical results, techniques and applications. The book promises to be especially rewarding for readers with an interest in the focus areas of applied linear algebra, probability and statistics.Table of ContentsChapter 1. On Some Matrix Versions of Covariance, Harmonic Mean and other Inequalities: An Overview.- Chapter 2. The Impact of Professor C. R. Rao's Research used in solving problems in Applied Probability.- Chapter 3. Upper ounds for the Euclidean distances between the BLUEs under the partitioned linear fixed model and the corresponding mixed model.- Chapter 4. Nucleolus Computation for some Structured TU Games via Graph Theory and Linear Algebra.- Chapter 5. From Linear System of Equations to Artificial Intelligence - The evolution Journey of Computer Tomographic Image Reconstruction Algorithms.- Chapter 6. Shapley Value and other Axiomatic Extensions to Shapley Value.- Chapter 7. An Accelerated Block Randomized Kaczmarz Methos.- Chapter 8. Nullity of Graphs - A Survey and Some New Results.- Chapter 9. Some Observations on Algebraic Connectivity of Graphs.- Chapter 10. Orthogonality for iadjoints f Operators.- Chapter 11. Permissible covariance structures for simultaneous retention of BLUEs in small and big linear models.- Chapter 12. On some Special Matrices and its Applications in Linear Complementarity Problem.- Chapter 3. On Nearest Matrix with Partially Specified Eigen Structure.- Chapter 14. Equality of BLUEs for Full, Small, and Intermediate Linear Models under Covariance Change, with links to Data Confidentiality and Encryption.-Chapter 15. Statistical Inference for Middle Censored Data with Applications. etc
£113.99
Springer Verlag, Singapore WAIC and WBIC with Python Stan: 100 Exercises for
Book SynopsisMaster the art of machine learning and data science by diving into the essence of mathematical logic with this comprehensive textbook. This book focuses on the widely applicable information criterion (WAIC), also described as the Watanabe-Akaike information criterion, and the widely applicable Bayesian information criterion (WBIC), also described as the Watanabe Bayesian information criterion. The book expertly guides you through relevant mathematical problems while also providing hands-on experience with programming in Python and Stan. Whether you’re a data scientist looking to refine your model selection process or a researcher who wants to explore the latest developments in Bayesian statistics, this accessible guide will give you a firm grasp of Watanabe Bayesian Theory.The key features of this indispensable book include: A clear and self-contained writing style, ensuring ease of understanding for readers at various levels of expertise. 100 carefully selected exercises accompanied by solutions in the main text, enabling readers to effectively gauge their progress and comprehension. A comprehensive guide to Sumio Watanabe’s groundbreaking Bayes theory, demystifying a subject once considered too challenging even for seasoned statisticians. Detailed source programs and Stan codes that will enhance readers’ grasp of the mathematical concepts presented. A streamlined approach to algebraic geometry topics in Chapter 6, making Bayes theory more accessible and less daunting. Embark on your machine learning and data science journey with this essential textbook and unlock the full potential of WAIC and WBIC today!Table of ContentsOver view of Watanabe's Bayes.- Introduction to Watanabe Bayesian Theory.- MCMC and Stan.- Mathematical Preparation.- Regular Statistical Models.- Information Criteria.- Algebraic Geometry.- The Essence of WAOIC.- WBIC and Its Application to Machine Learning.
£42.74
Springer Verlag, Singapore Statistics and Data Analysis for Engineers and
Book SynopsisThis textbook summarizes the different statistical, scientific, and financial data analysis methods for users ranging from a high school level to a professional level. It aims to combine the data analysis methods using three different programs—Microsoft Excel, SPSS, and MATLAB. The book combining the different data analysis tools is a unique approach. The book presents a variety of real-life problems in data analysis and machine learning, delivering the best solution. Analysis methods presented in this book include but are not limited to, performing various algebraic and trigonometric operations, regression modeling, and correlation, as well as plotting graphs and charts to represent the results. Fundamental concepts of applied statistics are also explained here, with illustrative examples. Thus, this book presents a pioneering solution to help a wide range of students, researchers, and professionals learn data processing, interpret different findings derived from the analyses, and apply them to their research or professional fields. The book also includes worked examples of practical problems. The primary focus behind designing these examples is understanding the concepts of data analysis and how it can solve problems. The chapters include practice exercises to assist users in enhancing their skills to execute statistical analysis calculations using software instead of relying on tables for probabilities and percentiles in the present world. Table of ContentsGeneral Overview.- Introduction to MATLAB.- The Fundamentals of Microsoft Excel.- Introduction to SPSS.
£999.99
Springer Nature Singapore Advanced Statistical Methods
Book Synopsis
£94.99
Independently Published Introductory Statistics 2e (hardcover, full color)
£63.99
Springer International Publishing AG An Introduction to Multivariable Mathematics
Book SynopsisThe text is designed for use in a forty-lecture introductory course covering linear algebra, multivariable differential calculus, and an introduction to real analysis. The core material of the book is arranged to allow for the main introductory material on linear algebra, including basic vector space theory in Euclidean space and the initial theory of matrices and linear systems, to be covered in the first ten or eleven lectures, followed by a similar number of lectures on basic multivariable analysis, including first theorems on differentiable functions on domains in Euclidean space and a brief introduction to submanifolds. The book then concludes with further essential linear algebra, including the theory of determinants, eigenvalues, and the spectral theorem for real symmetric matrices, and further multivariable analysis, including the contraction mapping principle and the inverse and implicit function theorems. There is also an appendix which provides a nine-lecture introduction to real analysis. There are various ways in which the additional material in the appendix could be integrated into a course--for example in the Stanford Mathematics honors program, run as a four-lecture per week program in the Autumn Quarter each year, the first six lectures of the nine-lecture appendix are presented at the rate of one lecture per week in weeks two through seven of the quarter, with the remaining three lectures per week during those weeks being devoted to the main chapters of the text. It is hoped that the text would be suitable for a quarter or semester course for students who have scored well in the BC Calculus advanced placement examination (or equivalent), particularly those who are considering a possible major in mathematics. The author has attempted to make the presentation rigorous and complete, with the clarity and simplicity needed to make it accessible to an appropriately large group of students. Table of Contents: Linear Algebra / Analysis in R / More Linear Algebra / More Analysis in R / Appendix: Introductory Lectures on Real AnalysisTable of ContentsLinear Algebra.- Analysis in R.- More Linear Algebra.- More Analysis in R.- Appendix: Introductory Lectures on Real Analysis.
£33.66
Elsevier Science Statistical Methods in the Atmospheric Sciences
Table of Contents1. Introduction2. Review of Probability3. Empirical Distributions and Exploratory Data Analysis4. Parametric Probability Distributions5. Frequentist Statistical Inference6. Bayesian Inference7. Statistical Forecasting8. Ensemble Forecasting9. Forecast Verification10. Time Series11. Matrix Algebra and Random Matrices12. Multivariate Normal Distribution13. Principal Component (EOF) Analysis14. Linear multivariate analysis of vector pairs: CCA, MCA, and RA15. Discrimination and Classification16. Cluster Analysis
£86.36
Taylor & Francis Statistics for Sports and Exercise Science
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£52.99
Taylor & Francis The Use Of Statistics In Forensic Science
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£999.99
Oxford University Press LikelihoodBased Inference in Cointegrated Vector Autoregressive Models
Book SynopsisThis book gives a detailed mathematical and statistical analysis of the cointegrated vector autoregresive model. This model had gained popularity because it can at the same time capture the short-run dynamic properties as well as the long-run equilibrium behaviour of many non-stationary time series. It also allows relevant economic questions to be formulated in a consistent statistical framework.Part I of the book is planned so that it can be used by those who want to apply the methods without going into too much detail about the probability theory. The main emphasis is on the derivation of estimators and test statistics through a consistent use of the Guassian likelihood function. It is shown that many different models can be formulated within the framework of the autoregressive model and the interpretation of these models is discussed in detail. In particular, models involving restrictions on the cointegration vectors and the adjustment coefficients are discussed, as well as the role
£66.50
Taylor & Francis Ltd Design of Mechanical Systems Based on Statistics A Guide to Improving Product Reliability Advanced Research in Reliability and System Assurance Engineering
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£142.50
Taylor & Francis Ltd Differential Equations in Engineering and Mechanics
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£169.84
Taylor & Francis Ltd Models for MultiState Survival Data
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£93.72
Taylor & Francis Ltd Advanced Survival Models Chapman HallCRC Biostatistics Series
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£114.00
Taylor & Francis Age Period and Cohort Effects Statistical Analysis and the Identification Problem
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£128.25
Taylor & Francis Age Period and Cohort Effects Statistical Analysis and the Identification Problem
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£37.99
Taylor & Francis Ltd Computer Intensive Methods in Statistics
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£52.24
Taylor & Francis Ltd Computer Intensive Methods in Statistics
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£142.50
Taylor & Francis Ltd Signal Detection for Medical Scientists
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£114.00
Taylor & Francis Ltd Statistical Concepts A First Course
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£128.25
Taylor & Francis Ltd R for Conservation and Development Projects
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£58.99
Taylor & Francis Ltd A First Course in Ergodic Theory
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£130.06
Taylor & Francis Ltd Advanced R Second Edition Chapman HallCRC The R Series
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£175.00
Taylor & Francis Ltd Cancer Clinical Trials
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£45.99
Taylor & Francis Ltd ProjectBased R Companion to Introductory Statistics
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£47.49
Taylor & Francis Ltd Supervised Machine Learning
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£114.00
Taylor & Francis Ltd Introduction to Stochastic Level Crossing Techniques
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£118.75
Taylor & Francis Ltd Statistical Methods for Handling Incomplete Data
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£105.00
Taylor & Francis Ltd Deep Learning in Time Series Analysis
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£120.00
Taylor & Francis Ltd Handbook of Methods for Designing Monitoring and Analyzing DoseFinding Trials Chapman HallCrc Handbooks of Modern Statistical Methods Aims and Scopes
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£68.39
Taylor & Francis Ltd Statistics for Making Decisions
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£109.25
Taylor & Francis Ltd Statistics for Making Decisions
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£42.74
Taylor & Francis Ltd Cybersecurity Analytics Chapman HallCRC Data Science Series
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£109.25
Taylor & Francis Ltd Randomization Bootstrap and Monte Carlo Methods in Biology Chapman HallCRC Texts in Statistical Science
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£120.00
Taylor & Francis Categorical Data Analysis for the Behavioral and Social Sciences
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£135.00
Taylor & Francis Ltd Statistical Methods for Mediation Confounding and Moderation Analysis Using R and SAS
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£135.00
Taylor & Francis Ltd SPSS Explained
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Taylor & Francis Ltd Spatializing Social Media
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Taylor & Francis Ltd Mathematics in Cyber Research
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Taylor & Francis Ltd Perfect Simulation
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Taylor & Francis Ltd Sharpening Your Advanced SAS Skills
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Taylor & Francis Ltd Pseudolinear Functions and Optimization
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Taylor & Francis Ltd A Handbook of Statistical Graphics Using SAS ODS
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Taylor & Francis Ltd Theory of Factorial Design Single and MultiStratum Experiments
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Taylor & Francis Ltd Foundations of Statistical Algorithms
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Taylor & Francis Ltd Fuzzy Multiple Objective Decision Making
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Taylor & Francis Ltd Applied Stochastic Processes
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