ABSTRACT
CHAPTER 8
Monte Carlo Methods
8.1 Background
This is the rst chapter specically about simulation techniques. Simula-
tion work in applied statistics replaces analytical work on behalf of the
researcher with repetitious, low-level eort by the computer. If a model
specication leads to a posterior form that is diÆcult or impossible to ma-
nipulate analytically, then it is often possible to create a set of simulated
values that share the same distributional properties, and describe the pos-
terior by using empirical summaries of these simulated values. This is an
old idea (see the 1951 chronicle; \Report on a Monte Carlo Calculation
Performed with the Eniac," by Mayer), but one that is particularly easy to
implement now that computers are ubiquitous and fast.
