Theory of Stochastic Objects

Athanasios Christou Micheas

ISBN 10: 1032242884 / ISBN 13: 9781032242880

Published by Chapman And Hall/CRC Dez 2021, 2021

About this Item

This item is printed on demand - it takes 3-4 days longer - Neuware -This book defines and investigates the concept of a random object. To accomplish this task in a natural way, it brings together three major areas; statistical inference, measure-theoretic probability theory and stochastic processes. This point of view has not been explored by existing textbooks; one would need material on real analysis, measure and probability theory, as well as stochastic processes - in addition to at least one text on statistics- to capture the detail and depth of material that has gone into this volume.Presents and illustrates 'random objects' in different contexts, under a unified framework, starting with rudimentary results on random variables and random sequences, all the way up to stochastic partial differential equations.Reviews rudimentary probability and introduces statistical inference, from basic to advanced, thus making the transition from basic statistical modeling and estimation to advanced topics more natural and concrete.Compact and comprehensive presentation of the material that will be useful to a reader from the mathematics and statistical sciences, at any stage of their career, either as a graduate student, an instructor, or an academician conducting research and requiring quick references and examples to classic topics. Includes 378 exercises, with the solutions manual available on the book's website.121 illustrative examples of the concepts presented in the text (many including multiple items in a single example).Thebook is targeted towards students at the master's and Ph.D. levels, as well as, academicians in the mathematics, statistics and related disciplines. Basic knowledge of calculus and matrix algebra is required. Prior knowledge of probability or measure theory is welcomed but not necessary. 410 pp. Englisch.

Seller Inventory # 9781032242880

Bibliographic Details

• Title: Theory of Stochastic Objects
• Publisher: Chapman And Hall/CRC Dez 2021
• Publication Date: 2021
• Language: English
• ISBN 10: 1032242884
• ISBN 13: 9781032242880
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 254W x 178H x 22D millimeters 254 millimeters width by 178 millimeters height by 22 millimeters depth
• Weight: 768 grams

About this title

Synopsis

This book defines and investigates the concept of a random object. To accomplish this task in a natural way, it brings together three major areas; statistical inference, measure-theoretic probability theory and stochastic processes. This point of view has not been explored by existing textbooks; one would need material on real analysis, measure and probability theory, as well as stochastic processes - in addition to at least one text on statistics- to capture the detail and depth of material that has gone into this volume.

• Presents and illustrates ‘random objects’ in different contexts, under a unified framework, starting with rudimentary results on random variables and random sequences, all the way up to stochastic partial differential equations.
• Reviews rudimentary probability and introduces statistical inference, from basic to advanced, thus making the transition from basic statistical modeling and estimation to advanced topics more natural and concrete.
• Compact and comprehensive presentation of the material that will be useful to a reader from the mathematics and statistical sciences, at any stage of their career, either as a graduate student, an instructor, or an academician conducting research and requiring quick references and examples to classic topics.
• Includes 378 exercises, with the solutions manual available on the book's website.
• 121 illustrative examples of the concepts presented in the text (many including multiple items in a single example).

The book is targeted towards students at the master’s and Ph.D. levels, as well as, academicians in the mathematics, statistics and related disciplines. Basic knowledge of calculus and matrix algebra is required. Prior knowledge of probability or measure theory is welcomed but not necessary.

About the Author

Athanasios Christou Micheas is Associate Professor of Statistics at the University of Missouri.