Empirical-bias bandwidths for spatial local polynomial regression with correlated errors
(2004) In Preprint without journal information- Abstract
- The empirical-bias bandwidth selector (EBBS) is a method for data-driven selection of bandwidths for local polynomial regression. It is a bandwidth selection method for estimation of the mean-function and its partial derivatives of any order as well as for estimation of the variance-function. Moreover EBBS allows for univariate as well as multivariate
predictor variables.
In this paper we introduce the empirical-bias bandwidth selector, EBBSdep. This estimation procedure is adjusted to allow for dependent errors and selection of diagonal or full bandwidth matrices for estimation of the mean-function or one of its partial derivatives as well as for estimation of the variance-function. Asymptotic results for the... (More) - The empirical-bias bandwidth selector (EBBS) is a method for data-driven selection of bandwidths for local polynomial regression. It is a bandwidth selection method for estimation of the mean-function and its partial derivatives of any order as well as for estimation of the variance-function. Moreover EBBS allows for univariate as well as multivariate
predictor variables.
In this paper we introduce the empirical-bias bandwidth selector, EBBSdep. This estimation procedure is adjusted to allow for dependent errors and selection of diagonal or full bandwidth matrices for estimation of the mean-function or one of its partial derivatives as well as for estimation of the variance-function. Asymptotic results for the conditional bias of the first order partial derivative
estimates are given for the local quadratic regression case.
A simulation study is performed to compare the adjusted and the original version of EBBS with theoretical results for a few cases displaying varying degrees of positive correlation. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/928966
- author
- Lindström, Torgny LU
- organization
- publishing date
- 2004
- type
- Contribution to journal
- publication status
- unpublished
- subject
- in
- Preprint without journal information
- issue
- 2004:11
- publisher
- Manne Siegbahn Institute
- ISSN
- 0348-7911
- language
- English
- LU publication?
- yes
- id
- e5a65f79-b103-4a9e-9d67-0f8c30b8ce42 (old id 928966)
- date added to LUP
- 2016-04-04 09:38:52
- date last changed
- 2018-11-21 20:54:36
@article{e5a65f79-b103-4a9e-9d67-0f8c30b8ce42, abstract = {{The empirical-bias bandwidth selector (EBBS) is a method for data-driven selection of bandwidths for local polynomial regression. It is a bandwidth selection method for estimation of the mean-function and its partial derivatives of any order as well as for estimation of the variance-function. Moreover EBBS allows for univariate as well as multivariate <br/><br> predictor variables. <br/><br> In this paper we introduce the empirical-bias bandwidth selector, EBBSdep. This estimation procedure is adjusted to allow for dependent errors and selection of diagonal or full bandwidth matrices for estimation of the mean-function or one of its partial derivatives as well as for estimation of the variance-function. Asymptotic results for the conditional bias of the first order partial derivative <br/><br> estimates are given for the local quadratic regression case. <br/><br> A simulation study is performed to compare the adjusted and the original version of EBBS with theoretical results for a few cases displaying varying degrees of positive correlation.}}, author = {{Lindström, Torgny}}, issn = {{0348-7911}}, language = {{eng}}, number = {{2004:11}}, publisher = {{Manne Siegbahn Institute}}, series = {{Preprint without journal information}}, title = {{Empirical-bias bandwidths for spatial local polynomial regression with correlated errors}}, year = {{2004}}, }