Author: Robert A. Wijsman
Publisher: IMS
ISBN: 9780940600195
Category : Mathematics
Languages : en
Pages : 264
Book Description
Invariant Measures on Groups and Their Use in Statistics
Author: Robert A. Wijsman
Publisher: IMS
ISBN: 9780940600195
Category : Mathematics
Languages : en
Pages : 264
Book Description
Publisher: IMS
ISBN: 9780940600195
Category : Mathematics
Languages : en
Pages : 264
Book Description
Examples and Problems in Mathematical Statistics
Author: Shelemyahu Zacks
Publisher: John Wiley & Sons
ISBN: 1118605837
Category : Mathematics
Languages : en
Pages : 499
Book Description
Provides the necessary skills to solve problems in mathematical statistics through theory, concrete examples, and exercises With a clear and detailed approach to the fundamentals of statistical theory, Examples and Problems in Mathematical Statistics uniquely bridges the gap between theory andapplication and presents numerous problem-solving examples that illustrate the relatednotations and proven results. Written by an established authority in probability and mathematical statistics, each chapter begins with a theoretical presentation to introduce both the topic and the important results in an effort to aid in overall comprehension. Examples are then provided, followed by problems, and finally, solutions to some of the earlier problems. In addition, Examples and Problems in Mathematical Statistics features: Over 160 practical and interesting real-world examples from a variety of fields including engineering, mathematics, and statistics to help readers become proficient in theoretical problem solving More than 430 unique exercises with select solutions Key statistical inference topics, such as probability theory, statistical distributions, sufficient statistics, information in samples, testing statistical hypotheses, statistical estimation, confidence and tolerance intervals, large sample theory, and Bayesian analysis Recommended for graduate-level courses in probability and statistical inference, Examples and Problems in Mathematical Statistics is also an ideal reference for applied statisticians and researchers.
Publisher: John Wiley & Sons
ISBN: 1118605837
Category : Mathematics
Languages : en
Pages : 499
Book Description
Provides the necessary skills to solve problems in mathematical statistics through theory, concrete examples, and exercises With a clear and detailed approach to the fundamentals of statistical theory, Examples and Problems in Mathematical Statistics uniquely bridges the gap between theory andapplication and presents numerous problem-solving examples that illustrate the relatednotations and proven results. Written by an established authority in probability and mathematical statistics, each chapter begins with a theoretical presentation to introduce both the topic and the important results in an effort to aid in overall comprehension. Examples are then provided, followed by problems, and finally, solutions to some of the earlier problems. In addition, Examples and Problems in Mathematical Statistics features: Over 160 practical and interesting real-world examples from a variety of fields including engineering, mathematics, and statistics to help readers become proficient in theoretical problem solving More than 430 unique exercises with select solutions Key statistical inference topics, such as probability theory, statistical distributions, sufficient statistics, information in samples, testing statistical hypotheses, statistical estimation, confidence and tolerance intervals, large sample theory, and Bayesian analysis Recommended for graduate-level courses in probability and statistical inference, Examples and Problems in Mathematical Statistics is also an ideal reference for applied statisticians and researchers.
Algebraic Methods in Statistics and Probability
Author: Marlos A. G. Viana
Publisher: American Mathematical Soc.
ISBN: 0821826875
Category : Mathematics
Languages : en
Pages : 354
Book Description
The 23 papers report recent developments in using the technique to help clarify the relationship between phenomena and data in a number of natural and social sciences. Among the topics are a coordinate-free approach to multivariate exponential families, some rank-based hypothesis tests for covariance structure and conditional independence, deconvolution density estimation on compact Lie groups, random walks on regular languages and algebraic systems of generating functions, and the extendibility of statistical models. There is no index. c. Book News Inc.
Publisher: American Mathematical Soc.
ISBN: 0821826875
Category : Mathematics
Languages : en
Pages : 354
Book Description
The 23 papers report recent developments in using the technique to help clarify the relationship between phenomena and data in a number of natural and social sciences. Among the topics are a coordinate-free approach to multivariate exponential families, some rank-based hypothesis tests for covariance structure and conditional independence, deconvolution density estimation on compact Lie groups, random walks on regular languages and algebraic systems of generating functions, and the extendibility of statistical models. There is no index. c. Book News Inc.
Group Invariance Applications in Statistics
Author: Morris L. Eaton
Publisher: IMS
ISBN: 9780940600157
Category : Group theory
Languages : en
Pages : 148
Book Description
Publisher: IMS
ISBN: 9780940600157
Category : Group theory
Languages : en
Pages : 148
Book Description
Selected Proceedings of the Symposium on Inference for Stochastic Processes
Author: Ishwar V. Basawa
Publisher: IMS
ISBN: 9780940600515
Category : Mathematics
Languages : en
Pages : 370
Book Description
Publisher: IMS
ISBN: 9780940600515
Category : Mathematics
Languages : en
Pages : 370
Book Description
The Bayesian Choice
Author: Christian P. Robert
Publisher: Springer Science & Business Media
ISBN: 1475743149
Category : Mathematics
Languages : en
Pages : 444
Book Description
This graduate-level textbook covers both the basic ideas of statistical theory, and also some of the more modern and advanced topics of Bayesian statistics, such as complete class theorems, the Stein effect, hierarchical and empirical Bayes modelling, Monte Carlo integration, and Gibbs sampling. In translating the book from the original French, the author has taken the opportunity to add and update material, and to include many problems and exercises for students.
Publisher: Springer Science & Business Media
ISBN: 1475743149
Category : Mathematics
Languages : en
Pages : 444
Book Description
This graduate-level textbook covers both the basic ideas of statistical theory, and also some of the more modern and advanced topics of Bayesian statistics, such as complete class theorems, the Stein effect, hierarchical and empirical Bayes modelling, Monte Carlo integration, and Gibbs sampling. In translating the book from the original French, the author has taken the opportunity to add and update material, and to include many problems and exercises for students.
Testing Statistical Hypotheses
Author: E.L. Lehmann
Publisher: Springer Nature
ISBN: 3030705781
Category : Mathematics
Languages : en
Pages : 1016
Book Description
The third edition of Testing Statistical Hypotheses updates and expands upon the classic graduate text, emphasizing optimality theory for hypothesis testing and confidence sets. The principal additions include a rigorous treatment of large sample optimality, together with the requisite tools. In addition, an introduction to the theory of resampling methods such as the bootstrap is developed. The sections on multiple testing and goodness of fit testing are expanded. The text is suitable for Ph.D. students in statistics and includes over 300 new problems out of a total of more than 760.
Publisher: Springer Nature
ISBN: 3030705781
Category : Mathematics
Languages : en
Pages : 1016
Book Description
The third edition of Testing Statistical Hypotheses updates and expands upon the classic graduate text, emphasizing optimality theory for hypothesis testing and confidence sets. The principal additions include a rigorous treatment of large sample optimality, together with the requisite tools. In addition, an introduction to the theory of resampling methods such as the bootstrap is developed. The sections on multiple testing and goodness of fit testing are expanded. The text is suitable for Ph.D. students in statistics and includes over 300 new problems out of a total of more than 760.
An Introduction to Bayesian Analysis
Author: Jayanta K. Ghosh
Publisher: Springer Science & Business Media
ISBN: 0387354336
Category : Mathematics
Languages : en
Pages : 356
Book Description
This is a graduate-level textbook on Bayesian analysis blending modern Bayesian theory, methods, and applications. Starting from basic statistics, undergraduate calculus and linear algebra, ideas of both subjective and objective Bayesian analysis are developed to a level where real-life data can be analyzed using the current techniques of statistical computing. Advances in both low-dimensional and high-dimensional problems are covered, as well as important topics such as empirical Bayes and hierarchical Bayes methods and Markov chain Monte Carlo (MCMC) techniques. Many topics are at the cutting edge of statistical research. Solutions to common inference problems appear throughout the text along with discussion of what prior to choose. There is a discussion of elicitation of a subjective prior as well as the motivation, applicability, and limitations of objective priors. By way of important applications the book presents microarrays, nonparametric regression via wavelets as well as DMA mixtures of normals, and spatial analysis with illustrations using simulated and real data. Theoretical topics at the cutting edge include high-dimensional model selection and Intrinsic Bayes Factors, which the authors have successfully applied to geological mapping. The style is informal but clear. Asymptotics is used to supplement simulation or understand some aspects of the posterior.
Publisher: Springer Science & Business Media
ISBN: 0387354336
Category : Mathematics
Languages : en
Pages : 356
Book Description
This is a graduate-level textbook on Bayesian analysis blending modern Bayesian theory, methods, and applications. Starting from basic statistics, undergraduate calculus and linear algebra, ideas of both subjective and objective Bayesian analysis are developed to a level where real-life data can be analyzed using the current techniques of statistical computing. Advances in both low-dimensional and high-dimensional problems are covered, as well as important topics such as empirical Bayes and hierarchical Bayes methods and Markov chain Monte Carlo (MCMC) techniques. Many topics are at the cutting edge of statistical research. Solutions to common inference problems appear throughout the text along with discussion of what prior to choose. There is a discussion of elicitation of a subjective prior as well as the motivation, applicability, and limitations of objective priors. By way of important applications the book presents microarrays, nonparametric regression via wavelets as well as DMA mixtures of normals, and spatial analysis with illustrations using simulated and real data. Theoretical topics at the cutting edge include high-dimensional model selection and Intrinsic Bayes Factors, which the authors have successfully applied to geological mapping. The style is informal but clear. Asymptotics is used to supplement simulation or understand some aspects of the posterior.
Testing Statistical Hypotheses
Author: Erich L. Lehmann
Publisher: Springer Science & Business Media
ISBN: 038727605X
Category : Mathematics
Languages : en
Pages : 795
Book Description
The third edition of Testing Statistical Hypotheses updates and expands upon the classic graduate text, emphasizing optimality theory for hypothesis testing and confidence sets. The principal additions include a rigorous treatment of large sample optimality, together with the requisite tools. In addition, an introduction to the theory of resampling methods such as the bootstrap is developed. The sections on multiple testing and goodness of fit testing are expanded. The text is suitable for Ph.D. students in statistics and includes over 300 new problems out of a total of more than 760.
Publisher: Springer Science & Business Media
ISBN: 038727605X
Category : Mathematics
Languages : en
Pages : 795
Book Description
The third edition of Testing Statistical Hypotheses updates and expands upon the classic graduate text, emphasizing optimality theory for hypothesis testing and confidence sets. The principal additions include a rigorous treatment of large sample optimality, together with the requisite tools. In addition, an introduction to the theory of resampling methods such as the bootstrap is developed. The sections on multiple testing and goodness of fit testing are expanded. The text is suitable for Ph.D. students in statistics and includes over 300 new problems out of a total of more than 760.
R.R. Bahadur's Lectures on the Theory of Estimation
Author: Raghu Raj Bahadur
Publisher: IMS
ISBN: 9780940600539
Category : Mathematics
Languages : en
Pages : 90
Book Description
"In the Winter Quarter of the academic year 1984-1985, Raj Bahadur gave a series of lectures on estimation theory at the University of Chicago"--Page i.
Publisher: IMS
ISBN: 9780940600539
Category : Mathematics
Languages : en
Pages : 90
Book Description
"In the Winter Quarter of the academic year 1984-1985, Raj Bahadur gave a series of lectures on estimation theory at the University of Chicago"--Page i.