A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output From a Computer Code
Michael D. McKay, Richard J. Beckman, W. J. Conover
Abstract
Two types of sampling plans are examined as alternatives to simple random sampling in Monte Carlo studies. These plans are shown to be improvements over simple random sampling with respect to variance for a class of estimators which includes the sample mean and the empirical distribution function.
Topics & Concepts
Simple random sampleEstimatorStatisticsMonte Carlo methodSampling (signal processing)MathematicsSimple (philosophy)Variance (accounting)Code (set theory)Sampling designComputer scienceImportance samplingSample (material)Programming languageSet (abstract data type)Filter (signal processing)Computer visionPopulationEpistemologyChromatographyAccountingDemographyChemistryBusinessSociologyPhilosophyProbability and Risk ModelsStatistical Distribution Estimation and ApplicationsFinancial Risk and Volatility Modeling