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Basics Of Modern Mathematical Statistics


Author : Vladimir Spokoiny
language : en
Publisher: Springer
Release Date : 2014-10-25


PDF Download Basics Of Modern Mathematical Statistics Books For free written by Vladimir Spokoiny and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-25 with Mathematics categories.


This textbook provides a unified and self-contained presentation of the main approaches to and ideas of mathematical statistics. It collects the basic mathematical ideas and tools needed as a basis for more serious study or even independent research in statistics. The majority of existing textbooks in mathematical statistics follow the classical asymptotic framework. Yet, as modern statistics has changed rapidly in recent years, new methods and approaches have appeared. The emphasis is on finite sample behavior, large parameter dimensions, and model misspecifications. The present book provides a fully self-contained introduction to the world of modern mathematical statistics, collecting the basic knowledge, concepts and findings needed for doing further research in the modern theoretical and applied statistics. This textbook is primarily intended for graduate and postdoc students and young researchers who are interested in modern statistical methods.

Modern Mathematical Statistics With Applications


Author : Jay L. Devore
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-12-07


PDF Download Modern Mathematical Statistics With Applications Books For free written by Jay L. Devore and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-12-07 with Mathematics categories.


Modern Mathematical Statistics with Applications, Second Edition strikes a balance between mathematical foundations and statistical practice. In keeping with the recommendation that every math student should study statistics and probability with an emphasis on data analysis, accomplished authors Jay Devore and Kenneth Berk make statistical concepts and methods clear and relevant through careful explanations and a broad range of applications involving real data. The main focus of the book is on presenting and illustrating methods of inferential statistics that are useful in research. It begins with a chapter on descriptive statistics that immediately exposes the reader to real data. The next six chapters develop the probability material that bridges the gap between descriptive and inferential statistics. Point estimation, inferences based on statistical intervals, and hypothesis testing are then introduced in the next three chapters. The remainder of the book explores the use of this methodology in a variety of more complex settings. This edition includes a plethora of new exercises, a number of which are similar to what would be encountered on the actuarial exams that cover probability and statistics. Representative applications include investigating whether the average tip percentage in a particular restaurant exceeds the standard 15%, considering whether the flavor and aroma of Champagne are affected by bottle temperature or type of pour, modeling the relationship between college graduation rate and average SAT score, and assessing the likelihood of O-ring failure in space shuttle launches as related to launch temperature.

Classic Topics On The History Of Modern Mathematical Statistics


Author : Prakash Gorroochurn
language : en
Publisher: John Wiley & Sons
Release Date : 2016-04-04


PDF Download Classic Topics On The History Of Modern Mathematical Statistics Books For free written by Prakash Gorroochurn and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-04 with Mathematics categories.


Written in a direct and clear manner, Classic Topics on the History of Modern Mathematical Statistics: From Laplace to More Recent Times presents a comprehensive guide to the history of mathematical statistics and details the major results and crucial developments over a 200-year period. Presented in chronological order, the book features an account of the classical and modern works that are essential to understanding the applications of mathematical statistics. Divided into three parts, the book begins with extensive coverage of the probabilistic works of Laplace, who laid much of the foundations of later developments in statistitical theory. Subsequently, the second part introduces 20th century statistical developments including work from Karl Pearson, Student, Fisher, and Neyman. Lastly, the author addresses post-Fisherian developments. -- from back cover.

Modern Math Matical Statistics


Author : Edward J. Dudewicz
language : en
Publisher: John Wiley & Sons Inc
Release Date : 1988


PDF Download Modern Math Matical Statistics Books For free written by Edward J. Dudewicz and has been published by John Wiley & Sons Inc this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988 with Business & Economics categories.


This modern treatment of mathematical statistics is concise, yet detailed enough to give readers a solid foundation in all aspects of the field. Treatment of each topic is thorough enough to make the coverage self-contained for a course in probability, and exceptional care has been taken to balance theory with applications. In addition to classical probability theory, such modern topics as order statistics and limiting distributions are discussed, along with applied examples from a wide variety of fields. Discussions include the core mathematical statistics topics of estimation, testing, and confidence intervals; ranking and selection procedures; decision theory; nonparametric statistics; regression and ANOVA; and robust statistical procedures. Computer-assisted data analysis is discussed at several points, reflecting the importance of statistical computation to the field. FORTRAN programs and BMDP routines are included, as well as the highly popular SAS routines. Also looks at the potential contribution of expert systems to statistics.

Mathematical Statistics


Author : A A Borokov
language : en
Publisher: CRC Press
Release Date : 1999-01-27


PDF Download Mathematical Statistics Books For free written by A A Borokov and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-01-27 with Mathematics categories.


A wide-ranging, extensive overview of modern mathematical statistics, this work reflects the current state of the field while being succinct and easy to grasp. The mathematical presentation is coherent and rigorous throughout. The author presents classical results and methods that form the basis of modern statistics, and examines the foundations of estimation theory, hypothesis testing theory and statistical game theory. He then considers statistical problems for two or more samples, and those in which observations are taken from different distributions. Methods of finding optimal and asymptotically optimal statistical procedures are given, along with treatments of homogeneity testing, regression, variance analysis and pattern recognition. The author also posits a number of methodological improvements that simplify proofs, and brings together a number of new results which have never before been published in a single monograph.

Mathematical Statistics With Applications In R


Author : Kandethody M. Ramachandran
language : en
Publisher: Elsevier
Release Date : 2014-09-14


PDF Download Mathematical Statistics With Applications In R Books For free written by Kandethody M. Ramachandran and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-14 with Mathematics categories.


Mathematical Statistics with Applications in R, Second Edition, offers a modern calculus-based theoretical introduction to mathematical statistics and applications. The book covers many modern statistical computational and simulation concepts that are not covered in other texts, such as the Jackknife, bootstrap methods, the EM algorithms, and Markov chain Monte Carlo (MCMC) methods such as the Metropolis algorithm, Metropolis-Hastings algorithm and the Gibbs sampler. By combining the discussion on the theory of statistics with a wealth of real-world applications, the book helps students to approach statistical problem solving in a logical manner. This book provides a step-by-step procedure to solve real problems, making the topic more accessible. It includes goodness of fit methods to identify the probability distribution that characterizes the probabilistic behavior or a given set of data. Exercises as well as practical, real-world chapter projects are included, and each chapter has an optional section on using Minitab, SPSS and SAS commands. The text also boasts a wide array of coverage of ANOVA, nonparametric, MCMC, Bayesian and empirical methods; solutions to selected problems; data sets; and an image bank for students. Advanced undergraduate and graduate students taking a one or two semester mathematical statistics course will find this book extremely useful in their studies. Step-by-step procedure to solve real problems, making the topic more accessible Exercises blend theory and modern applications Practical, real-world chapter projects Provides an optional section in each chapter on using Minitab, SPSS and SAS commands Wide array of coverage of ANOVA, Nonparametric, MCMC, Bayesian and empirical methods

Mathematical Statistics


Author : Jun Shao
language : en
Publisher: Springer Science & Business Media
Release Date : 2003-07-17


PDF Download Mathematical Statistics Books For free written by Jun Shao and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-07-17 with Mathematics categories.


This graduate textbook covers topics in statistical theory essential for graduate students preparing for work on a Ph.D. degree in statistics. The first chapter provides a quick overview of concepts and results in measure-theoretic probability theory that are usefulin statistics. The second chapter introduces some fundamental concepts in statistical decision theory and inference. Chapters 3-7 contain detailed studies on some important topics: unbiased estimation, parametric estimation, nonparametric estimation, hypothesis testing, and confidence sets. A large number of exercises in each chapter provide not only practice problems for students, but also many additional results. In addition to the classical results that are typically covered in a textbook of a similar level, this book introduces some topics in modern statistical theory that have been developed in recent years, such as Markov chain Monte Carlo, quasi-likelihoods, empirical likelihoods, statistical functionals, generalized estimation equations, the jackknife, and the bootstrap. Jun Shao is Professor of Statistics at the University of Wisconsin, Madison. Also available: Jun Shao and Dongsheng Tu, The Jackknife and Bootstrap, Springer- Verlag New York, Inc., 1995, Cloth, 536 pp., 0-387-94515-6.