Yu, K. and Jones, M.C.
(2004).
| DOI (Digital Object Identifier) Link: | https://doi.org/10.1198/016214504000000133 |
|---|---|
| Google Scholar: | Look up in Google Scholar |
Abstract
We consider estimation of mean and variance functions with kernel-weighted local polynomial fitting in a heteroscedastic nonparametric regression model. Our preferred estimators are based on a localized normal likelihood, using a standard local linear form for estimating the mean and a local log-linear form for estimating the variance. It is important to allow two bandwidths in this problem, separate ones for mean and variance estimation. We provide data-based methods for choosing the bandwidths. We also consider asymptotic results, and study and use them. The methodology is compared with a popular competitor and is seen to perform better for small and moderate sample sizes in simulations. A brief example is provided.
| Item Type: | Journal Item |
|---|---|
| ISSN: | 1537-274X |
| Keywords: | bandwidth selection; heteroscedasticity; kernel estimation; nonparametric regression |
| Academic Unit/School: | Faculty of Science, Technology, Engineering and Mathematics (STEM) > Mathematics and Statistics Faculty of Science, Technology, Engineering and Mathematics (STEM) |
| Item ID: | 2130 |
| Depositing User: | M. C. Jones |
| Date Deposited: | 05 Jun 2006 |
| Last Modified: | 07 Dec 2018 08:51 |
| URI: | http://oro.open.ac.uk/id/eprint/2130 |
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