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ConfidenceInterval Estimation Using QuasiIndependent Sequences
 IIE Transactions. To Appear
"... A quasiindependent (QI) subsequence is a subset of timeseries observations obtained by systematic sampling. Because the observations appear to be independent, as determined by the runs tests, classical statistical techniques can be used on those observations directly. This paper discusses implemen ..."
Abstract

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A quasiindependent (QI) subsequence is a subset of timeseries observations obtained by systematic sampling. Because the observations appear to be independent, as determined by the runs tests, classical statistical techniques can be used on those observations directly. This paper discusses implementation of a sequential procedure to determine the simulation run length to obtain a QI subsequence, and the batch size for constructing confidence intervals for an estimator of the steadystate mean of a stochastic process. Our QI procedure increases the simulation run length and batch size progressively until a certain number of essentially independent and identically distributed samples are obtained. The only (mild) assumption is that the correlations of the stochastic process output sequence eventually die off as the lag increases. An experimental performance evaluation demonstrates the validity of the QI procedure. 1.
An Enhanced TwoStage Selection Procedure
, 2000
"... This paper discusses implementation of a twostage procedure to determine the simulation run length for selecting the best of k designs. We purpose an Enhanced TwoStage Selection (ETSS) procedure. The number of additional replications at the second stage for each design is determined by both the va ..."
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This paper discusses implementation of a twostage procedure to determine the simulation run length for selecting the best of k designs. We purpose an Enhanced TwoStage Selection (ETSS) procedure. The number of additional replications at the second stage for each design is determined by both the variances of the sample means and the differences of the sample means of alternative designs. We show that the ETSS procedure gives valid selections with significantly reduced simulation replications compared to Rinott's procedure. An experimental performance evaluation demonstrates the validity of the ETSS procedure.
ABSTRACT EXPERIMENTAL PERFORMANCE EVALUATION OF HISTOGRAM APPROXIMATION FOR SIMULATION OUTPUT ANALYSIS
"... We summarize the results of an experimental performance evaluation of using an empirical histogram to approximate the steadystate distribution of the underlying stochastic process. We use a runs test to determine the required sample size for simulation output analysis and construct a histogram by c ..."
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We summarize the results of an experimental performance evaluation of using an empirical histogram to approximate the steadystate distribution of the underlying stochastic process. We use a runs test to determine the required sample size for simulation output analysis and construct a histogram by computing sample quantiles at certain grid points. The algorithm dynamically increases the sample size so that histogram estimates are asymptotically unbiased. Characteristics of the steadystate distribution, such as the mean and variance, can then be estimated through the empirical histogram. The preliminary experimental results indicate that the natural estimators obtained based on the empirical distribution are fairly accurate. 1
Computer Science and Software Engineering,
"... Abstract. Steady state simulation is used to study longrun behavior. Usually only the expected value of the steady state probability distribution function is estimated. In many cases quantiles of this distribution are of higher interest. In this paper a new usage of quantile estimators is proposed, ..."
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Abstract. Steady state simulation is used to study longrun behavior. Usually only the expected value of the steady state probability distribution function is estimated. In many cases quantiles of this distribution are of higher interest. In this paper a new usage of quantile estimators is proposed, which is derived from mean value analysis and is based on multiple independent replications. The advantage in using multiple independent replications is discussed, especially their ability to detect the steady state phase of quantiles. 1
Simulation Output Analysis Via Dynamic Batch Means
, 2000
"... This paper is focused on estimating the quality of the sample mean from a steadystate simulation experiment with consideration of computational efficiency, memory requirement, and statistical efficiency. In addition, we seek methods that do not require knowing run length a priori. We develop an alg ..."
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This paper is focused on estimating the quality of the sample mean from a steadystate simulation experiment with consideration of computational efficiency, memory requirement, and statistical efficiency. In addition, we seek methods that do not require knowing run length a priori. We develop an algorithm of nonoverlapping batch means that is implemented in fixed memory by dynamically changing both batch size and number of batches as the simulation runs. The algorithm, denoted by DBM for Dynamic Batch Means, requires computation time similar to other batch means datacollection methods, despite its fixed memory requirement. To achieve satisfactory statistical efficiency of DBM, we propose two associated estimators, VPBM , of the variance of the sample mean and investigate their statistical properties. Our study shows that the estimator parameter w 1 is, as a practical matter, better than the other proposed estimators.