隨機過程探究

內(nèi)容概要

　　while this is a book about harry and his
adventurous life, it is primarily a serious text about stochastic
processes. it features the basic stochas-tic processes that are
necessary ingredients for building models of a wide variety of
phenomena exhibiting time varying randomness.
　　the book is intended as a first year graduate text for courses
usually called stochastic processes (perhaps amended by the words
"applied" or "introduction to ... ") or applied probability, or
sometimes stochastic modelling. it is meant to be very accessible
to beginners, and at the same time, to serve those who come to the
course with strong backgrounds. this flexiblity also permits the
instructor to push the sophistication level up or down. for the
novice, discussions and motivation are given carefully and in great
detail. in some sections beginners are advised to skip certain
devel-opments, while in others, they can read the words and skip
the symbols in order to get the content without more technical
detail than they are ready to assimilate. in fact, with the
numerous readings and variety of prob-lems, it is easy to carve a
path so that the book challenges more advanced students, but
remains instructive and manageable for beginners. some sections are
starred and come with a warning that they contain material which is
more mathematically demanding. several discussions have been
modularized to facilitate flexible adaptation to the needs of
students with differing backgrounds. the text makes crystal clear
distinctions between the following: proofs, partial proofs,
motivations, plausibility arguments and good old fashioned
hand-waving.

作者簡介

作者：（美國）雷斯尼克（Sidney I.Resnick）

書籍目錄

preface
chapter 1. preliminaries: discrete index sets and/or discrete state
spaces
　1.1. non-negative integer valued random variables
　1.2. convolution
　1.3. generating functions
　　1.3.1. differentiation of generating functions
　　1.3.2. generating functions and moments
　　1.3.3. generating functions and convolution
　　1.3.4. generating functions, compounding and random sums
　1.4. the simple branching process
　1.5. limit distributions and the continuity theorem
　　1.5.1. the law of rare events
　1.6. the simple random walk
　1.7. the distribution of a process*
　1.8. stopping times*
　　1.8.1. wald's identity
　　1.8.2. splitting an lid sequence at a stopping time
　exercises for chapter 1
chapter 2. markov chains
　2.1. construction and first properties
　2.2. examples
　2.3. higher order transition probabilities
　2.4. decomposition of the state space
　2.5. the dissection principle
　2.6. transience and recurrence
　2.7. periodicity
　2.8. solidarity properties
　2.9. examples
　2.10. canonical decomposition
　2.11. absorption probabilities
　2.12. invariant measures and stationary distributions
　　2.12.1. time averages
　2.13. limit distributions
　　2.13.1 more on null recurrence and transience*
　2.14. computation of the stationary distribution
　2.15. classification techniques
　exercises for chapter 2
chapter 3. renewal theory
　3.1. basics
　3.2. analytic interlude
　　3.2.1. integration
　　3.2.2. convolution
　　3.2.3. laplace transforms
　3.3. counting renewals
　3.4. renewal reward processes
　3.5. the renewal equation
　　3.5.1. risk processes*
　3.6. the poisson process as a renewal process
　3.7. informal discussion of renewal limit theorems;regenerative
processes
　　3.7.1 an informal discussion of regenerative processes
　3.8. discrete renewal theory
　3.9. stationary renewal processes*
　3.10. blackwell and key renewal theorems*
　　3.10.1. direct riemann integrability*
　　3.10.2. equivalent forms of the renewal theorems*
　　3.10.3. proof of the renewal theorem*
　3.11. improper renewal equations
　3.12. more regenerative processes*
　　3.12.1. definitions and examples*
　　3.12.2. the renewal equation and smith's theorem*
　　3.12.3. queueing examples
　exercises for chapter 3
chapter 4.point processes
　4.1. basics
　4.2. the poisson process
　4.3. transforming poisson processes
　　4.3.1. max-stable and stable random variables*
　4.4. more transformation theory; marking and thinning
　4.5. the order statistic property
　4.6. variants of the poiason process
　4.7. wec. hnlcal basics*
　　4.7.1. the laplace functional*
　4.8. more on the poisson process*
　4.9. a general construction of the poisson process;a simple
derivation of the order statistic property*
　4.10. more transformation theory; location dependent
thinning*
　4.11. records*
　exercises for chapter 4
chapter 5.continuous time markov chains
　5.1. definitions and construction
　5.2. stability and explosions
　　5.2.1. the markov property*
　5.3. dissection
　　5.3.1. more detail on dissection*
　5.4. the backward equation and the generator matrix
　5.5. stationary and limiting distributions
　　5.5.1. more on invariant measures*
　5.6. laplace transform methods
　5.7. calculations and examples
　　5.7.1. queueing networks
　5.8. time dependent solutions*
　5.9. reversibility
　5.10. uniformizability
　5.11. the linear birth process as a point process
　exercises for chapter 5
chapter 6. brownian motion
　6.1. introduction
　6.2. preliminaries
　6.3. construction of brownian motion*
　6.4. simple properties of standard brownian motion
　6.5. the reflection principle and the distribution of the
maximum
　6.6. the strong independent increment property and
reflection*
　6.7. escape from a strip
　6.8. brownian motion with drift
　6.9. heavy traffic approximations in queueing theory
　6.10. the brownian bridge and the kolmogorov-smirnov
statistic
　6.11. path properties*
　6.12. quadratic variation
　6.13. khintchine's law of the iterated logarithm for brownian
motion*
　exercises for chapter 6
chapter 7. the general random walk*
　7.1. stopping times
　7.2. global properties
　7.3. prelude to wiener-hopf: probabilistic interpretations of
transforms
　7.4. dual pairs of stopping times
　7.5. wiener-hopf decompositions
　7.6. consequences of the wiener-hopf factorization
　7.7. the maximum of a random walk
　7.8. random walks and the g/g/1 queue
　　7.8.1. exponential right tail
　　7.8.2. application to g/m/1 queueing model,
　　7.8.3. exponential left tail
　　7.8.4. the m/g/1 queue
　　7.8.5. queue lengths
references
index

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《隨機過程探究(英文)》表述靈活，大量的例子，練習和應用，并有的計算機程序作支持，使得內(nèi)容的立體感增強，易于理解，可以作為應用科學領域不同層次水平學生的對隨機過程的入門教程。

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