Through numerous real-world applications, this text explains how to construct, fit, and evaluate statistical and stochastic models for use in diverse areas such as geology, sociology, biology, and economics. It incorporates traditional statistical and probability theory with modern computational methods. Along with an updated bibliography and improved figures, this edition includes an extended discussion on Bayesian methods, a large number of new exercises, and a new appendix on computational methods. All of the data sets and MATLAB and R programs found in the text as well as lecture slides and other ancillary material are available for download at www.crcpress.com

Introduction and Examples. Basic Model Fitting. Function Optimisation. Basic Likelihood Tools. General Principles. Simulation Techniques. Bayesian Methods and MCMC. General Families of Models. Index of Data Sets. Index of MATLAB Programs. Appendices. Solutions and Comments for Selected Exercises. Bibliography. Index.