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Stochastic Processes - Inference Theory

✍ Scribed by Malempati M. Rao (auth.)

Publisher
Springer International Publishing
Year
2014
Tongue
English
Leaves
685
Series
Springer Monographs in Mathematics
Edition
2
Category
Library
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✦ Synopsis

This is the revised and enlarged 2nd edition of the authors’ original text, which was intended to be a modest complement to Grenander's fundamental memoir on stochastic processes and related inference theory. The present volume gives a substantial account of regression analysis, both for stochastic processes and measures, and includes recent material on Ridge regression with some unexpected applications, for example in econometrics.

The first three chapters can be used for a quarter or semester graduate course on inference on stochastic processes. The remaining chapters provide more advanced material on stochastic analysis suitable for graduate seminars and discussions, leading to dissertation or research work. In general, the book will be of interest to researchers in probability theory, mathematical statistics and electrical and information theory.

✦ Table of Contents

Front Matter....Pages i-xvii
Introduction and Preliminaries....Pages 1-18
Principles of Hypothesis Testing....Pages 19-72
Parameter Estimation and Asymptotics....Pages 73-131
Inference for Classes of Processes....Pages 133-222
Likelihood Ratios for Processes....Pages 223-338
Sampling and Regression for Processes....Pages 339-406
More on Stochastic Inference....Pages 407-488
Prediction and Filtering of Processes....Pages 489-580
Nonparametric Estimation for Processes....Pages 581-623
Back Matter....Pages 625-669

✦ Subjects

Probability Theory and Stochastic Processes; Statistics, general; Measure and Integration; Fourier Analysis; Applications of Mathematics

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