Estimation of a density in a simulation model

Ann-Kathrin Bott, Tina Felber and Michael Kohler

Journal of Nonparametric Statistics, 2015, vol. 27, issue 3, 271-285

Abstract: The problem of estimating density in a simulation model is considered. Given a value of an -valued random input parameter X , the value of a real-valued random variable is computed. Here is a function which measures the quality of a technical system with input X . It is assumed that X and Y have densities. Given a sample of , the task is to estimate the density of Y . In a first step we estimate m and the density of X . Using these estimators we compute in a second step an estimator of the density of Y . Results concerning the -consistency and the rate of convergence are proven and the finite sample behaviour of the estimators is illustrated by applying them to simulated and real data.

Date: 2015
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DOI: 10.1080/10485252.2015.1049601

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