An Introduction to Statistical Computing: A Simulation-based Approach

A comprehensive introduction to sampling-based methods in statistical computing

The use of computers in mathematics and statistics has opened up a wide range of techniques for studying otherwise intractable problems.  Sampling-based simulation techniques are now an invaluable tool for exploring statistical models.  This book gives a comprehensive introduction to the exciting area of sampling-based methods.

An Introduction to Statistical Computing introduces the classical topics of random number generation and Monte Carlo methods.  It also includes some advanced methods such as the reversible jump Markov chain Monte Carlo algorithm and modern methods such as approximate Bayesian computation and multilevel Monte Carlo techniques

Avainsanat: Computational & Graphical Statistics, An Introduction to Statistical Computing: A Simulation-based Approach, reversible jump MCMC and multi-level Monte Carlo, generation of random numbers, non-uniform random variates, stochastic processes, Markov Chain Monte Carlo Methods, Continuous-Time Models