¹Katholieke Universiteit Leuven, Leuven, Belgium

Correspondence: J Martens, Faculty of Economics and Applied Economics, Katholieke Universiteit Leuven, Naamsestraat 69, 3000 Leuven, Belgium. E-mail: jurgen_martens@skynet.be

Received April 2007; Accepted February 2008; Published online 14 May 2008.

Abstract

A simulation study often requires computation of a point estimate and confidence region for the steady-state mean of a stochastic output process. The literature offers a variety of statistical techniques, including replication/deletion, the batch-means method, and spectrum analysis. We present a new multivariate output-analysis technique that is based on the general autoregressive time-series model with exogenous variables to set up a joint confidence region for the steady-state mean. We demonstrate our technique by an extensive computational experiment, and show that it performs at least as well as other output-analysis techniques, without having some of their drawbacks.