Lectures on the Theory of Stochastic Processes

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Format: Paperback
Pub. Date: 1996-12-01
Publisher(s): De Gruyter
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Table of Contents

Prefacep. 1
Stochastic Processes. Definitions. Examplesp. 3
The Kolmogorov consistency theorem. Classification of processesp. 8
Random Walks. Recurrence. Reneweal Theoremp. 14
Martingales. Inequalities for martingalesp. 21
Theorems on the limit of a martingalep. 27
Stationary sequences. Ergodic theoremp. 34
Ergodic theorem. Metric transitivityp. 39
Regularization of a process. Continuityp. 44
Processes without discontinuities of the second kindp. 50
Continuity of processes with independent increments. Martingales with continuous timep. 56
Measurable processesp. 61
Stopping times. Associated [sigma]-algebrasp. 65
Completely measurable processesp. 69
L[subscript 2]-theoryp. 73
Stochastic integralsp. 80
Stationary processes. Spectral representationsp. 87
Stationary sequences. Regularity and singularityp. 93
The prediction of a stationary sequencep. 98
Markov processesp. 104
Homogeneous Markov processes and associated semigroupsp. 110
Homogeneous purely discontinuous processes. Conditions for their regularityp. 115
Processes with a denumerable set of statesp. 120
Simple birth and death processesp. 127
Branching processes with particles of only one kindp. 132
Homogeneous processes and strongly continuous semigroups. Resolvent operator and generatorp. 137
The Hille-Iosida theoremp. 143
Processes with independent increments. Representation of the discontinuous partp. 149
General representation of a stochastically continuous process with independent incrementsp. 155
Diffusion processesp. 160
Stochastic integralsp. 166
Existence, uniqueness, and properties of solutions of stochastic differential equationsp. 172
Ito's formula with some corollariesp. 178
Referencesp. 184
Table of Contents provided by Blackwell. All Rights Reserved.

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