Estimation of a density in a simulation model
| Autor: | Ann-Kathrin Bott, Michael Kohler, Tina Felber |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Statistics and Probability
Mathematical optimization Rate of convergence Consistency (statistics) Estimator Applied mathematics Density estimation Function (mathematics) Statistics Probability and Uncertainty Random variable Multivariate kernel density estimation Mathematics Nonparametric regression |
| Zdroj: | Journal of Nonparametric Statistics. 27:271-285 |
| ISSN: | 1029-0311 1048-5252 |
| DOI: | 10.1080/10485252.2015.1049601 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|