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Stationary Processes and Discrete Parameter Markov Processes

Overview of attention for book
Stationary Processes and Discrete Parameter Markov Processes
Springer International Publishing

Table of Contents

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    Book Overview
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    Chapter 2 Weakly Stationary Processes and Their Spectral Measures
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    Chapter 3 Spectral Representation of Stationary Processes
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    Chapter 4 Birkhoff’s Ergodic Theorem
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    Chapter 15 Martingale Central Limit Theorem
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    Chapter 16 Stationary Ergodic Markov Processes: SLLN & FCLT
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    Chapter 17 Linear Markov Processes
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    Chapter 18 Markov Processes Generated by Iterations of I.I.D. Maps
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    Chapter 19 A Splitting Condition and Geometric Rates of Convergence to Equilibrium
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    Chapter 20 Irreducibility and Harris Recurrent Markov Processes
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    Chapter 21 An Extended Perron–Frobenius Theorem and Large Deviation Theory for Markov Processes
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    Chapter 22 Special Topic: Applications of Large Deviation Theory
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    Chapter 23 Special Topic: Associated Random Fields, Positive Dependence, FKG Inequalities
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    Chapter 25 Special Topic: An Introduction to Kalman Filter
Attention for Chapter 18: Markov Processes Generated by Iterations of I.I.D. Maps
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Chapter title
Markov Processes Generated by Iterations of I.I.D. Maps
Chapter number 18
Book title
Stationary Processes and Discrete Parameter Markov Processes
Published by
Springer, Cham, January 2022
DOI 10.1007/978-3-031-00943-3_18
Book ISBNs
978-3-03-100941-9, 978-3-03-100943-3
Authors

Bhattacharya, Rabi, Waymire, Edward

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