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Statistical Inference Based On Divergence Measures
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Book Synopsis Statistical Inference Based on Divergence Measures by : Leandro Pardo
Download or read book Statistical Inference Based on Divergence Measures written by Leandro Pardo and published by CRC Press. This book was released on 2018-11-12 with total page 513 pages. Available in PDF, EPUB and Kindle. Book excerpt: The idea of using functionals of Information Theory, such as entropies or divergences, in statistical inference is not new. However, in spite of the fact that divergence statistics have become a very good alternative to the classical likelihood ratio test and the Pearson-type statistic in discrete models, many statisticians remain unaware of this p
Book Synopsis Statistical Inference Based on Divergence Measures by : Leandro Pardo
Download or read book Statistical Inference Based on Divergence Measures written by Leandro Pardo and published by Chapman and Hall/CRC. This book was released on 2005-10-10 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: The idea of using functionals of Information Theory, such as entropies or divergences, in statistical inference is not new. However, in spite of the fact that divergence statistics have become a very good alternative to the classical likelihood ratio test and the Pearson-type statistic in discrete models, many statisticians remain unaware of this powerful approach. Statistical Inference Based on Divergence Measures explores classical problems of statistical inference, such as estimation and hypothesis testing, on the basis of measures of entropy and divergence. The first two chapters form an overview, from a statistical perspective, of the most important measures of entropy and divergence and study their properties. The author then examines the statistical analysis of discrete multivariate data with emphasis is on problems in contingency tables and loglinear models using phi-divergence test statistics as well as minimum phi-divergence estimators. The final chapter looks at testing in general populations, presenting the interesting possibility of introducing alternative test statistics to classical ones like Wald, Rao, and likelihood ratio. Each chapter concludes with exercises that clarify the theoretical results and present additional results that complement the main discussions. Clear, comprehensive, and logically developed, this book offers a unique opportunity to gain not only a new perspective on some standard statistics problems, but the tools to put it into practice.
Book Synopsis New Developments in Statistical Information Theory Based on Entropy and Divergence Measures by : Leandro Pardo
Download or read book New Developments in Statistical Information Theory Based on Entropy and Divergence Measures written by Leandro Pardo and published by MDPI. This book was released on 2019-05-20 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents new and original research in Statistical Information Theory, based on minimum divergence estimators and test statistics, from a theoretical and applied point of view, for different statistical problems with special emphasis on efficiency and robustness. Divergence statistics, based on maximum likelihood estimators, as well as Wald’s statistics, likelihood ratio statistics and Rao’s score statistics, share several optimum asymptotic properties, but are highly non-robust in cases of model misspecification under the presence of outlying observations. It is well-known that a small deviation from the underlying assumptions on the model can have drastic effect on the performance of these classical tests. Specifically, this book presents a robust version of the classical Wald statistical test, for testing simple and composite null hypotheses for general parametric models, based on minimum divergence estimators.
Book Synopsis Statistical Inference by : Ayanendranath Basu
Download or read book Statistical Inference written by Ayanendranath Basu and published by CRC Press. This book was released on 2011-06-22 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: In many ways, estimation by an appropriate minimum distance method is one of the most natural ideas in statistics. However, there are many different ways of constructing an appropriate distance between the data and the model: the scope of study referred to by "Minimum Distance Estimation" is literally huge. Filling a statistical resource gap, Stati
Book Synopsis Statistical Topics and Stochastic Models for Dependent Data with Applications by : Vlad Stefan Barbu
Download or read book Statistical Topics and Stochastic Models for Dependent Data with Applications written by Vlad Stefan Barbu and published by John Wiley & Sons. This book was released on 2020-12-03 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collective volume authored by leading scientists in the field of stochastic modelling, associated statistical topics and corresponding applications. The main classes of stochastic processes for dependent data investigated throughout this book are Markov, semi-Markov, autoregressive and piecewise deterministic Markov models. The material is divided into three parts corresponding to: (i) Markov and semi-Markov processes, (ii) autoregressive processes and (iii) techniques based on divergence measures and entropies. A special attention is payed to applications in reliability, survival analysis and related fields.
Book Synopsis Some Basic Theory for Statistical Inference by : E.J.G. Pitman
Download or read book Some Basic Theory for Statistical Inference written by E.J.G. Pitman and published by CRC Press. This book was released on 2018-01-18 with total page 61 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book the author presents with elegance and precision some of the basic mathematical theory required for statistical inference at a level which will make it readable by most students of statistics.
Book Synopsis Statistical Inference: Based on the Likelihood by : Adelchi Azzalini
Download or read book Statistical Inference: Based on the Likelihood written by Adelchi Azzalini and published by . This book was released on 1996 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Statistical Inference from High Dimensional Data by : Carlos Fernandez-Lozano
Download or read book Statistical Inference from High Dimensional Data written by Carlos Fernandez-Lozano and published by MDPI. This book was released on 2021-04-28 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: • Real-world problems can be high-dimensional, complex, and noisy • More data does not imply more information • Different approaches deal with the so-called curse of dimensionality to reduce irrelevant information • A process with multidimensional information is not necessarily easy to interpret nor process • In some real-world applications, the number of elements of a class is clearly lower than the other. The models tend to assume that the importance of the analysis belongs to the majority class and this is not usually the truth • The analysis of complex diseases such as cancer are focused on more-than-one dimensional omic data • The increasing amount of data thanks to the reduction of cost of the high-throughput experiments opens up a new era for integrative data-driven approaches • Entropy-based approaches are of interest to reduce the dimensionality of high-dimensional data
Book Synopsis Theory of Statistical Inference and Information by : Igor Vajda
Download or read book Theory of Statistical Inference and Information written by Igor Vajda and published by Springer. This book was released on 1989-02-28 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Statistical Inference Based on Ranks by : Thomas P. Hettmansperger
Download or read book Statistical Inference Based on Ranks written by Thomas P. Hettmansperger and published by . This book was released on 1984-07-30 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: A coherent, unified set of statistical methods, based on ranks, for analyzing data resulting from various experimental designs. Uses MINITAB, a statistical computing system for the implementation of the methods. Assesses the statistical and stability properties of the methods through asymptotic efficiency and influence curves and tolerance values. Includes exercises and problems.
Book Synopsis Applied Reliability Engineering and Risk Analysis by : Ilia B. Frenkel
Download or read book Applied Reliability Engineering and Risk Analysis written by Ilia B. Frenkel and published by John Wiley & Sons. This book was released on 2013-08-22 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: This complete resource on the theory and applications of reliability engineering, probabilistic models and risk analysis consolidates all the latest research, presenting the most up-to-date developments in this field. With comprehensive coverage of the theoretical and practical issues of both classic and modern topics, it also provides a unique commemoration to the centennial of the birth of Boris Gnedenko, one of the most prominent reliability scientists of the twentieth century. Key features include: expert treatment of probabilistic models and statistical inference from leading scientists, researchers and practitioners in their respective reliability fields detailed coverage of multi-state system reliability, maintenance models, statistical inference in reliability, systemability, physics of failures and reliability demonstration many examples and engineering case studies to illustrate the theoretical results and their practical applications in industry Applied Reliability Engineering and Risk Analysis is one of the first works to treat the important areas of degradation analysis, multi-state system reliability, networks and large-scale systems in one comprehensive volume. It is an essential reference for engineers and scientists involved in reliability analysis, applied probability and statistics, reliability engineering and maintenance, logistics, and quality control. It is also a useful resource for graduate students specialising in reliability analysis and applied probability and statistics. Dedicated to the Centennial of the birth of Boris Gnedenko, renowned Russian mathematician and reliability theorist
Book Synopsis Data Analysis and Related Applications, Volume 1 by : Konstantinos N. Zafeiris
Download or read book Data Analysis and Related Applications, Volume 1 written by Konstantinos N. Zafeiris and published by John Wiley & Sons. This book was released on 2022-08-17 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: The scientific field of data analysis is constantly expanding due to the rapid growth of the computer industry and the wide applicability of computational and algorithmic techniques, in conjunction with new advances in statistical, stochastic and analytic tools. There is a constant need for new, high-quality publications to cover the recent advances in all fields of science and engineering. This book is a collective work by a number of leading scientists, computer experts, analysts, engineers, mathematicians, probabilists and statisticians who have been working at the forefront of data analysis and related applications. The chapters of this collaborative work represent a cross-section of current concerns, developments and research interests in the above scientific areas. The collected material has been divided into appropriate sections to provide the reader with both theoretical and applied information on data analysis methods, models and techniques, along with related applications.
Book Synopsis Robust Procedures for Estimating and Testing in the Framework of Divergence Measures by : Leandro Pardo
Download or read book Robust Procedures for Estimating and Testing in the Framework of Divergence Measures written by Leandro Pardo and published by Mdpi AG. This book was released on 2021-09-23 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: The scope of the contributions to this book will be to present new and original research papers based on MPHIE, MHD, and MDPDE, as well as test statistics based on these estimators from a theoretical and applied point of view in different statistical problems with special emphasis on robustness. Manuscripts given solutions to different statistical problems as model selection criteria based on divergence measures or in statistics for high-dimensional data with divergence measures as loss function are considered. Reviews making emphasis in the most recent state-of-the art in relation to the solution of statistical problems base on divergence measures are also presented.
Book Synopsis Introduction to the Theory of Statistical Inference by : Hannelore Liero
Download or read book Introduction to the Theory of Statistical Inference written by Hannelore Liero and published by CRC Press. This book was released on 2016-04-19 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based on the authors' lecture notes, this text presents concise yet complete coverage of statistical inference theory, focusing on the fundamental classical principles. Unlike related textbooks, it combines the theoretical basis of statistical inference with a useful applied toolbox that includes linear models. Suitable for a second semester undergraduate course on statistical inference, the text offers proofs to support the mathematics and does not require any use of measure theory. It illustrates core concepts using cartoons and provides solutions to all examples and problems.
Book Synopsis Advances in Data Analysis by : Christos H. Skiadas
Download or read book Advances in Data Analysis written by Christos H. Skiadas and published by Springer Science & Business Media. This book was released on 2009-11-25 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unified volume is a collection of invited chapters presenting recent developments in the field of data analysis, with applications to reliability and inference, data mining, bioinformatics, lifetime data, and neural networks. The book is a useful reference for graduate students, researchers, and practitioners in statistics, mathematics, engineering, economics, social science, bioengineering, and bioscience.
Book Synopsis Fundamental Statistical Inference by : Marc S. Paolella
Download or read book Fundamental Statistical Inference written by Marc S. Paolella and published by John Wiley & Sons. This book was released on 2018-06-19 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: A hands-on approach to statistical inference that addresses the latest developments in this ever-growing field This clear and accessible book for beginning graduate students offers a practical and detailed approach to the field of statistical inference, providing complete derivations of results, discussions, and MATLAB programs for computation. It emphasizes details of the relevance of the material, intuition, and discussions with a view towards very modern statistical inference. In addition to classic subjects associated with mathematical statistics, topics include an intuitive presentation of the (single and double) bootstrap for confidence interval calculations, shrinkage estimation, tail (maximal moment) estimation, and a variety of methods of point estimation besides maximum likelihood, including use of characteristic functions, and indirect inference. Practical examples of all methods are given. Estimation issues associated with the discrete mixtures of normal distribution, and their solutions, are developed in detail. Much emphasis throughout is on non-Gaussian distributions, including details on working with the stable Paretian distribution and fast calculation of the noncentral Student's t. An entire chapter is dedicated to optimization, including development of Hessian-based methods, as well as heuristic/genetic algorithms that do not require continuity, with MATLAB codes provided. The book includes both theory and nontechnical discussions, along with a substantial reference to the literature, with an emphasis on alternative, more modern approaches. The recent literature on the misuse of hypothesis testing and p-values for model selection is discussed, and emphasis is given to alternative model selection methods, though hypothesis testing of distributional assumptions is covered in detail, notably for the normal distribution. Presented in three parts—Essential Concepts in Statistics; Further Fundamental Concepts in Statistics; and Additional Topics—Fundamental Statistical Inference: A Computational Approach offers comprehensive chapters on: Introducing Point and Interval Estimation; Goodness of Fit and Hypothesis Testing; Likelihood; Numerical Optimization; Methods of Point Estimation; Q-Q Plots and Distribution Testing; Unbiased Point Estimation and Bias Reduction; Analytic Interval Estimation; Inference in a Heavy-Tailed Context; The Method of Indirect Inference; and, as an appendix, A Review of Fundamental Concepts in Probability Theory, the latter to keep the book self-contained, and giving material on some advanced subjects such as saddlepoint approximations, expected shortfall in finance, calculation with the stable Paretian distribution, and convergence theorems and proofs.
Book Synopsis Introductory Statistical Inference by : Nitis Mukhopadhyay
Download or read book Introductory Statistical Inference written by Nitis Mukhopadhyay and published by CRC Press. This book was released on 2006-02-07 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introductory Statistical Inference develops the concepts and intricacies of statistical inference. With a review of probability concepts, this book discusses topics such as sufficiency, ancillarity, point estimation, minimum variance estimation, confidence intervals, multiple comparisons, and large-sample inference. It introduces techniques of two-stage sampling, fitting a straight line to data, tests of hypotheses, nonparametric methods, and the bootstrap method. It also features worked examples of statistical principles as well as exercises with hints. This text is suited for courses in probability and statistical inference at the upper-level undergraduate and graduate levels.
