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STOCHASTIC MODELS WITH APPLICATIONS TO GENETICS, CANCERS, AIDS AND OTHER BIOMEDICAL SYSTEMS
by Tan Wai-Yuan (University of Memphis, USA)
Table of Contents (195k)
Preface (78k)
Chapter 1: Introduction
Chapter 1.1: Some Basic Concepts of Stochastic Processes and Examples (187k)
Chapter 1.2: Markovian and Non-Markovian Processes, Markov Chains and Examples (317k)
Chapter 1.3: Diffusion Processes and Examples (183k)
Chapter 1.4: State Space Models and Hidden Markov Models (191k)
Chapter 1.5: The Scope of the Book (145k)
Chapter 1.6: Complements and Exercises (205k)
This book presents a systematic treatment of Markov chains, diffusion processes and state space models, as well as alternative approaches to Markov chains through stochastic difference equations and stochastic differential equations. It illustrates how these processes and approaches are applied to many problems in genetics, carcinogenesis, AIDS epidemiology and other biomedical systems.
One feature of the book is that it describes the basic MCMC (Markov chain and Monte Carlo) procedures and illustrates how to use the Gibbs sampling method and the multilevel Gibbs sampling method to solve many problems in genetics, carcinogenesis, AIDS and other biomedical systems.
As another feature, the book develops many state space models for many genetic problems, carcinogenesis, AIDS epidemiology and HIV pathogenesis. It shows in detail how to use the multilevel Gibbs sampling method to estimate (or predict) simultaneously the state variables and the unknown parameters in cancer chemotherapy, carcinogenesis, AIDS epidemiology and HIV pathogenesis. As a matter of fact, this book is the first to develop many state space models for many genetic problems, carcinogenesis and other biomedical problems.
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