Large-sample normality of the batch-means variance estimator

DOI10.1016/S0167-6377(02)00156-6zbMath1009.62072MaRDI QIDQ1866993

Yanyan Li

Publication date: 2 April 2003

Published in: Operations Research Letters (Search for Journal in Brave)

zbMATH Keywords

stationary processesvariance estimationsteady-state simulationbatch-means estimator

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Non-Markovian processes: estimation (62M09)

Related Items (2)

Estimating accuracy of the MCMC variance estimator: asymptotic normality for batch means estimators ⋮ Strong invariance principles for ergodic Markov processes

Cites Work

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• The use of subseries values for estimating the variance of a general statistic from a stationary sequence
• Estimating the asymptotic variance with batch means
• Batch Size Effects in the Analysis of Simulation Output
• An Investigation of Finite-Sample Behavior of Confidence Interval Estimators
• The estimation of standard errors in Monte Carlo simulation experiments
• Moment bounds for stationary mixing sequences
• Large-Sample Results for Batch Means
• Planning Queueing Simulations
• Optimal Mean-Squared-Error Batch Sizes
• Mean-Square Consistency of the Variance Estimator in Steady-State Simulation Output Analysis
• Estimation of the mean of a stationary time series by sampling

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