ABSTRACT

Highlighting modern computational methods, Applied Stochastic Modelling, Second Edition provides students with the practical experience of scientific computing in applied statistics through a range of interesting real-world applications. It also successfully revises standard probability and statistical theory. Along with an updated bibliography and

chapter 1|16 pages

Introduction and Examples

chapter 2|28 pages

Basic Model-Fitting

chapter 3|32 pages

Function Optimisation

chapter 4|46 pages

Basic Likelihood Tools

chapter 5|46 pages

General Principles

chapter 6|30 pages

Simulation Techniques

chapter 7|38 pages

Bayesian Methods and MCMC

chapter 8|26 pages

General Families of Models