Theory and Methods of Statistics

Book Theory and Methods of Statistics Cover

Read or download book entitled Theory and Methods of Statistics written by P.K. Bhattacharya and published by Academic Press in PDF, EPUB and Kindle Format. Click Get This Book button to download or read online books. Join over 650.000 happy Readers and READ as many books as you like. We cannot guarantee that Theory and Methods of Statistics book is available in the library.

  • Publisher : Academic Press
  • Release : 23 June 2016
  • ISBN : 9780128041239
  • Page : 544 pages
  • Rating : 4.5/5 from 103 voters

Download Theory and Methods of Statistics in PDF, Epub and Kindle

Theory and Methods of Statistics covers essential topics for advanced graduate students and professional research statisticians. This comprehensive resource covers many important areas in one manageable volume, including core subjects such as probability theory, mathematical statistics, and linear models, and various special topics, including nonparametrics, curve estimation, multivariate analysis, time series, and resampling. The book presents subjects such as "maximum likelihood and sufficiency," and is written with an intuitive, heuristic approach to build reader comprehension. It also includes many probability inequalities that are not only useful in the context of this text, but also as a resource for investigating convergence of statistical procedures. Codifies foundational information in many core areas of statistics into a comprehensive and definitive resource Serves as an excellent text for select master’s and PhD programs, as well as a professional reference Integrates numerous examples to illustrate advanced concepts Includes many probability inequalities useful for investigating convergence of statistical procedures

GET THIS BOOK

Theory and Methods of Statistics

Theory and Methods of Statistics
  • Author : P.K. Bhattacharya,Prabir Burman
  • Publisher : Academic Press
  • Release Date : 2016-06-23
  • ISBN : 9780128041239
GET THIS BOOKTheory and Methods of Statistics

Theory and Methods of Statistics covers essential topics for advanced graduate students and professional research statisticians. This comprehensive resource covers many important areas in one manageable volume, including core subjects such as probability theory, mathematical statistics, and linear models, and various special topics, including nonparametrics, curve estimation, multivariate analysis, time series, and resampling. The book presents subjects such as "maximum likelihood and sufficiency," and is written with an intuitive, heuristic approach to build reader comprehension. It also includes many probability

Robust Statistics

Robust Statistics
  • Author : Ricardo A. Maronna,R. Douglas Martin,Victor J. Yohai,Matías Salibián-Barrera
  • Publisher : John Wiley & Sons
  • Release Date : 2019-01-04
  • ISBN : 9781119214687
GET THIS BOOKRobust Statistics

A new edition of this popular text on robust statistics, thoroughly updated to include new and improved methods and focus on implementation of methodology using the increasingly popular open-source software R. Classical statistics fail to cope well with outliers associated with deviations from standard distributions. Robust statistical methods take into account these deviations when estimating the parameters of parametric models, thus increasing the reliability of fitted models and associated inference. This new, second edition of Robust Statistics: Theory and Methods (

Model Selection and Multimodel Inference

Model Selection and Multimodel Inference
  • Author : Kenneth P. Burnham,David R. Anderson
  • Publisher : Springer Science & Business Media
  • Release Date : 2007-05-28
  • ISBN : 9780387224565
GET THIS BOOKModel Selection and Multimodel Inference

A unique and comprehensive text on the philosophy of model-based data analysis and strategy for the analysis of empirical data. The book introduces information theoretic approaches and focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. It contains several new approaches to estimating model selection uncertainty and incorporating selection uncertainty into estimates of precision. An array of examples is given to illustrate various technical issues.

Statistics for High-Dimensional Data

Statistics for High-Dimensional Data
  • Author : Peter Bühlmann,Sara van de Geer
  • Publisher : Springer Science & Business Media
  • Release Date : 2011-06-08
  • ISBN : 9783642201929
GET THIS BOOKStatistics for High-Dimensional Data

Modern statistics deals with large and complex data sets, and consequently with models containing a large number of parameters. This book presents a detailed account of recently developed approaches, including the Lasso and versions of it for various models, boosting methods, undirected graphical modeling, and procedures controlling false positive selections. A special characteristic of the book is that it contains comprehensive mathematical theory on high-dimensional statistics combined with methodology, algorithms and illustrations with real data examples. This in-depth approach highlights

An Introduction to Statistical Learning

An Introduction to Statistical Learning
  • Author : Gareth James,Daniela Witten,Trevor Hastie,Robert Tibshirani
  • Publisher : Springer Science & Business Media
  • Release Date : 2013-06-24
  • ISBN : 9781461471387
GET THIS BOOKAn Introduction to Statistical Learning

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more.

Statistical Hypothesis Testing

Statistical Hypothesis Testing
  • Author : Ning-Zhong Shi,Jian Tao
  • Publisher : World Scientific
  • Release Date : 2008
  • ISBN : 9789812814364
GET THIS BOOKStatistical Hypothesis Testing

This book presents up-to-date theory and methods of statistical hypothesis testing based on measure theory. The so-called statistical space is a measurable space adding a family of probability measures. Most topics in the book will be developed based on this term. The book includes some typical data sets, such as the relation between race and the death penalty verdict, the behavior of food intake of two kinds of Zucker rats, and the per capita income and expenditure in China during

Essential Statistical Inference

Essential Statistical Inference
  • Author : Dennis D. Boos,L A Stefanski
  • Publisher : Springer Science & Business Media
  • Release Date : 2013-02-06
  • ISBN : 9781461448181
GET THIS BOOKEssential Statistical Inference

​This book is for students and researchers who have had a first year graduate level mathematical statistics course. It covers classical likelihood, Bayesian, and permutation inference; an introduction to basic asymptotic distribution theory; and modern topics like M-estimation, the jackknife, and the bootstrap. R code is woven throughout the text, and there are a large number of examples and problems. An important goal has been to make the topics accessible to a wide audience, with little overt reliance on measure

The Methods of Distances in the Theory of Probability and Statistics

The Methods of Distances in the Theory of Probability and Statistics
  • Author : Svetlozar T. Rachev,Lev Klebanov,Stoyan V. Stoyanov,Frank Fabozzi
  • Publisher : Springer Science & Business Media
  • Release Date : 2013-01-04
  • ISBN : 9781461448693
GET THIS BOOKThe Methods of Distances in the Theory of Probability and Statistics

This book covers the method of metric distances and its application in probability theory and other fields. The method is fundamental in the study of limit theorems and generally in assessing the quality of approximations to a given probabilistic model. The method of metric distances is developed to study stability problems and reduces to the selection of an ideal or the most appropriate metric for the problem under consideration and a comparison of probability metrics. After describing the basic structure

Statistical Methods for Organizational Research

Statistical Methods for Organizational Research
  • Author : Chris Dewberry
  • Publisher : Routledge
  • Release Date : 2004-08-26
  • ISBN : 9781134314348
GET THIS BOOKStatistical Methods for Organizational Research

This clearly written textbook clarifies the concepts underpinning descriptive and inferential statistics in organizational research. Acting as much more than a theoretical reference tool, step-by-step it guides readers through the various key stages of successful data analysis. Covering everything from introductory descriptive statistics to advanced inferential techniques such as ANOVA, multiple and logistic regression and factor analysis, this is one of the most comprehensive textbooks available. Using examples directly relevant to organizational research it includes practical advice on such topics

Robust Statistics

Robust Statistics
  • Author : Ricardo A. Maronna,Douglas R. Martin,Victor J. Yohai
  • Publisher : Wiley
  • Release Date : 2006-05-12
  • ISBN : 0470010924
GET THIS BOOKRobust Statistics

Classical statistical techniques fail to cope well with deviations from a standard distribution. Robust statistical methods take into account these deviations while estimating the parameters of parametric models, thus increasing the accuracy of the inference. Research into robust methods is flourishing, with new methods being developed and different applications considered. Robust Statistics sets out to explain the use of robust methods and their theoretical justification. It provides an up-to-date overview of the theory and practical application of the robust statistical

Asymptotic Methods in Statistical Decision Theory

Asymptotic Methods in Statistical Decision Theory
  • Author : Lucien Le Cam
  • Publisher : Springer Science & Business Media
  • Release Date : 2012-12-06
  • ISBN : 9781461249467
GET THIS BOOKAsymptotic Methods in Statistical Decision Theory

This book grew out of lectures delivered at the University of California, Berkeley, over many years. The subject is a part of asymptotics in statistics, organized around a few central ideas. The presentation proceeds from the general to the particular since this seemed the best way to emphasize the basic concepts. The reader is expected to have been exposed to statistical thinking and methodology, as expounded for instance in the book by H. Cramer [1946] or the more recent text by

Multiple Comparisons

Multiple Comparisons
  • Author : Jason Hsu
  • Publisher : CRC Press
  • Release Date : 1996-02-01
  • ISBN : 0412982811
GET THIS BOOKMultiple Comparisons

Multiple Comparisons introduces simultaneous statistical inference and covers the theory and techniques for all-pairwise comparisons, multiple comparisons with the best, and multiple comparisons with a control. The author describes confidence intervals methods and stepwise exposes abuses and misconceptions, and guides readers to the correct method for each problem. Discussions also include the connections with bioequivalence, drug stability, and toxicity studies Real data sets analyzed by computer software packages illustrate the applications presented.

Theory-Based Data Analysis for the Social Sciences

Theory-Based Data Analysis for the Social Sciences
  • Author : Carol S. Aneshensel
  • Publisher : SAGE
  • Release Date : 2013
  • ISBN : 9781412994354
GET THIS BOOKTheory-Based Data Analysis for the Social Sciences

This book presents the elaboration model for the multivariate analysis of observational quantitative data. This model entails the systematic introduction of "third variables" to the analysis of a focal relationship between one independent and one dependent variable to ascertain whether an inference of causality is justified. Two complementary strategies are used: an exclusionary strategy that rules out alternative explanations such as spuriousness and redundancy with competing theories, and an inclusive strategy that connects the focal relationship to a network of

Time Series: Theory and Methods

Time Series: Theory and Methods
  • Author : Peter J. Brockwell,Richard A. Davis
  • Publisher : Springer Science & Business Media
  • Release Date : 2009-05-13
  • ISBN : 9781441903204
GET THIS BOOKTime Series: Theory and Methods

This edition contains a large number of additions and corrections scattered throughout the text, including the incorporation of a new chapter on state-space models. The companion diskette for the IBM PC has expanded into the software package ITSM: An Interactive Time Series Modelling Package for the PC, which includes a manual and can be ordered from Springer-Verlag. * We are indebted to many readers who have used the book and programs and made suggestions for improvements. Unfortunately there is not enough

Complex Models and Computational Methods in Statistics

Complex Models and Computational Methods in Statistics
  • Author : Matteo Grigoletto,Francesco Lisi,Sonia Petrone
  • Publisher : Springer Science & Business Media
  • Release Date : 2013-01-26
  • ISBN : 9788847028715
GET THIS BOOKComplex Models and Computational Methods in Statistics

The use of computational methods in statistics to face complex problems and highly dimensional data, as well as the widespread availability of computer technology, is no news. The range of applications, instead, is unprecedented. As often occurs, new and complex data types require new strategies, demanding for the development of novel statistical methods and suggesting stimulating mathematical problems. This book is addressed to researchers working at the forefront of the statistical analysis of complex systems and using computationally intensive statistical