Convergence Properties of the Batch Means Method for Simulation Output Analysis

Convergence Properties of the Batch Means Method for Simulation Output Analysis

We examine key convergence properties of the steady-state simulation analysis method of nonoverlapping batch means (NOBM) when it is applied to a stationary, phi-mixing process. For an increasing batch size and a fixed batch count, we show that the standardized vector of batch means converges in distribution to a vector of independent standard normal variates—a well-known result underlying the ...

Asap2: an Improved Batch Means Procedure for Simulation Output Analysis

We introduce ASAP2, an improved variant of the batchmeans algorithm ASAP for steady-state simulation output analysis. ASAP2 operates as follows: the batch size is progressively increased until the batch means pass the ShapiroWilk test for multivariate normality; and then ASAP2 delivers a correlation-adjusted confidence interval. The latter adjustment is based on an inverted Cornish-Fisher expan...

An Improved Batch Means Procedure for Simulation Output Analysis

We formulate and evaluate the Automated Simulation Analysis Procedure (ASAP), an algorithm for steady-state simulation output analysis based on the method of nonoverlapping batch means (NOBM). ASAP delivers a confidence interval for an expected response that is centered on the sample mean of a portion of a simulation-generated time series and satisfies a user-specified absolute or relative prec...

On Databased Choice of Batch Size for Simulation Output Analysis

The use of batch means is a well known technique for estimating the variance of point estimators computed from simulation experiments. The batch means variance estimator is simply the (appropriately scaled) sample variance of the estimator computed on subsets of consecutive observations. For the method to be practical, a good choice of batch length is necessary. We propose a method to estimate ...

Batch Size Effects in the Analysis of Simulation Output