Quantile and histogram estimation

12 years 3 months ago
Quantile and histogram estimation
This paper discusses implementation of a sequential procedure to construct proportional half-width confidence intervals for a simulation estimator of the steady-state quantiles and histograms of a stochastic process. Our quasiindependent (QI) procedure increases the simulation run length progressively until a certain number of essentially independent and identically distributed samples are obtained. We compute sample quantiles at certain grid points and use Lagrange interpolation to estimate the p quantile. It is known that order statistics quantile estimator is asymptotically unbiased when the output sequences satisfy certain conditions. Even though the proposed sequential procedure is a heuristic procedure, it does have strong basis. Our empirical results show that the procedure gives quantile estimates and histograms that satisfy a pre-specified precision requirement. An experimental performance evaluation demonstrates the validity of using the QI procedure to estimate the quantile...
E. Jack Chen, W. David Kelton
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2001
Where WSC
Authors E. Jack Chen, W. David Kelton
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