On New Developments in Statistical Inference for Measures of Divergence
Title | On New Developments in Statistical Inference for Measures of Divergence PDF eBook |
Author | Kyriakos Matthaiou |
Publisher | |
Pages | 101 |
Release | 2007 |
Genre | Divergent series |
ISBN |
Statistical Inference Based on Divergence Measures
Title | Statistical Inference Based on Divergence Measures PDF eBook |
Author | Leandro Pardo |
Publisher | CRC Press |
Pages | 513 |
Release | 2018-11-12 |
Genre | Mathematics |
ISBN | 1420034812 |
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
New Developments in Statistical Information Theory Based on Entropy and Divergence Measures
Title | New Developments in Statistical Information Theory Based on Entropy and Divergence Measures PDF eBook |
Author | Leandro Pardo |
Publisher | MDPI |
Pages | 344 |
Release | 2019-05-20 |
Genre | Social Science |
ISBN | 3038979368 |
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.
Statistical Inference Based on Divergence Measures
Title | Statistical Inference Based on Divergence Measures PDF eBook |
Author | Leandro Pardo |
Publisher | Chapman and Hall/CRC |
Pages | 512 |
Release | 2005-10-10 |
Genre | Mathematics |
ISBN | 9781584886006 |
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.
Statistical Inference
Title | Statistical Inference PDF eBook |
Author | Ayanendranath Basu |
Publisher | CRC Press |
Pages | 424 |
Release | 2011-06-22 |
Genre | Computers |
ISBN | 1420099663 |
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
Statistical Topics and Stochastic Models for Dependent Data with Applications
Title | Statistical Topics and Stochastic Models for Dependent Data with Applications PDF eBook |
Author | Vlad Stefan Barbu |
Publisher | John Wiley & Sons |
Pages | 288 |
Release | 2020-12-03 |
Genre | Mathematics |
ISBN | 1786306034 |
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.
Geometry and Statistics
Title | Geometry and Statistics PDF eBook |
Author | |
Publisher | Academic Press |
Pages | 490 |
Release | 2022-07-15 |
Genre | Mathematics |
ISBN | 0323913466 |
Geometry and Statistics, Volume 46 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters written by an international board of authors. Provides the authority and expertise of leading contributors from an international board of authors Presents the latest release in the Handbook of Statistics series Updated release includes the latest information on Geometry and Statistics