<p><br/></p><p>作者：Siddhartha Chib&nbsp;&nbsp; Washington University, St. Louis MO, USA<br/>Edward Greenberg&nbsp;&nbsp; Washington University, St. Louis MO, USA<br/>时间：February, 1995</p><p>页数：31</p><p>Abstract<br/>We present several Markov chain Monte Carlo simulation methods that have been<br/>widely used in recent years in econometrics and statistics. Among these is the Gibbs<br/>sampler, which has been of particular interest to econometricians. Although the paper<br/>summarizes some of the relevant theoretical literature, its emphasis is on the presen-<br/>tation and explanation of applications to important models that are studied in econo-<br/>metrics. We include a discussion of some implementation issues, the use of the methods<br/>in connection with the EM algorithm, and how the methods can be helpful in model<br/>specication questions. Many of the applications of these methods are of particular<br/>interest to Bayesians, but we also point out ways in which frequentist statisticians may<br/>nd the techniques useful.</p>