Limit theorems for stochastic measures of the accuracy of density estimators |
| |
Authors: | Peter Hall |
| |
Affiliation: | Department of Statistics, Australian National University, Canberra City, A.C.T. 2600, Australia |
| |
Abstract: | Stochastic measures of the distance between a density f and its estimate fn have been used to compare the accuracy of density estimators in Monte Carlo trials. The practice in the past has been to select a measure largely on the basis of its ease of computation, using only heuristic arguments to explain the large sample behaviour of the measure. Steele [11] has shown that these arguments can lead to incorrect conclusions. In the present paper we obtain limit theorems for the stochastic processes derived from stochastic measures, thereby explaining the large sample behaviour of the measures. |
| |
Keywords: | Primary 60F05, 60G99, Secondary 62E20, 62G05 Laws of large numbers nonparametric density estimators stochastic processes limit theorems stochastic measures of accuracy |
本文献已被 ScienceDirect 等数据库收录! |
|