We propose test statistics based on kernel density estimation for testing the equality of scale parameters. The statistics are compared with other statistics with respect to the asymptotic relative e ciency. The statistics are more e cient than the c-sample analogs of the two-sample Mood test and th
Large deviations probabilities for a test of symmetry based on kernel density estimator
โ Scribed by Anna V. Osmoukhina
- Publisher
- Elsevier Science
- Year
- 2001
- Tongue
- English
- Weight
- 100 KB
- Volume
- 54
- Category
- Article
- ISSN
- 0167-7152
No coin nor oath required. For personal study only.
โฆ Synopsis
The goal is to prove large deviations limit theorems for statistics, which are based on kernel density estimator and which are designed for symmetry testing. The formulas for the rate functions of the pointwise di erence and the uniform norm of the di erence are expressed in terms of the underlying density function and their asymptotics are found.
๐ SIMILAR VOLUMES
Hall and Hart (1990) proved that the mean integrated squared error (MISE) of a marginal kernel density estimator from an infinite moving average process X1, )(2 .... may be decomposed into the sum of MISE of the same kernel estimator for a random sample of the same size and a term proportional to th