英文版的汽车软件工程-原理.过程.方法.工具，原汁原味。

A brief introduction to the formulation of various types of stochastic epidemic models is presented based on the well-known deterministic SIS and SIR epidemic models. Three different types of stochastic model formulations are discussed: discrete time Markov chain, continuous time Markov chain and stochastic differential equations. Properties unique to the stochastic models are presented: probability of disease extinction, probability of disease outbreak, quasistationary probability distribution, final size distribution, and expected duration of an epidemic. The chapter ends with a discussion of two stochastic formulations that cannot be directly related to the SIS and SIR epidemic models. They are discrete time Markov chain formulations applied in the study of epidemics within households (chain binomial models) and in the prediction of the initial spread of an epidemic (branching processes).

Stochastic Processes, Theory for Applications Robert G. Gallager著的随机过程的习题解答

A first course in stochastic processes (2ed., AP, 1975)Karlin S., Taylor

Introduction to Stochastic Processes 随机过程介绍

随机过程，英文版，第二版，Sheldoen Ross 编著 《随机过程(原书[第2版)》从概率的角度而不是分析的角度来看待随机过程，书中介绍了随机过程的基本理论，包括Poisson过程、Markov链、鞅、 Brown运动、随机序关系、Poisson逼近等，并阐明这些理论在各领域的应用

A Second Course in Stochastic Processes - Karlin & Taylor(1981)