N-Skart: A Nonsequential Skewness- and Autoregression-Adjusted Batch-Means Procedure for Simulation Analysis

作者：Tafazzoli Ali^*; Steiger Natalie M; Wilson James R

来源：IEEE Transactions on Automatic Control, 2011, 56(2): 254-264.

DOI：10.1109/TAC.2010.2052137

• Autoregressive representation
• confidence interval (CI)
• Cornish-Fisher expansion
• method of batch means
• simulation
• statistical analysis
• steady-state analysis

We discuss N-Skart, a nonsequential procedure designed to deliver a confidence interval (CI) for the steady-state mean of a simulation output process when the user supplies a single simulation-generated time series of arbitrary size and specifies the required coverage probability for a CI based on that data set. N-Skart is a variant of the method of batch means that exploits separate adjustments to the half-length of the CI so as to account for the effects on the distribution of the underlying Student's t-statistic that arise from skewness (nonnormality) and autocorrelation of the batch means. If the sample size is sufficiently large, then N-Skart delivers not only a CI but also a point estimator for the steady-state mean that is approximately free of initialization bias. In an experimental performance evaluation involving a wide range of test processes and sample sizes, N-Skart exhibited close conformance to the user-specified CI coverage probabilities.

• 出版日期2011-2