Local likelihood density estimation based on smooth truncation
Two existing density estimators based on local likelihood have properties that are comparable to those of local likelihood regression but they are much less used than their counterparts in regression. We consider truncation as a natural way of localising parametric density estimation. Based on this...
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| Formato: | artículo |
| Fecha de publicación: | 2006 |
| País: | España |
| Recursos: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/107330 |
| Acesso em linha: | https://hdl.handle.net/2117/107330 https://dx.doi.org/10.1093/biomet/93.2.472 |
| Access Level: | acceso abierto |
| Palavra-chave: | Local polynomial regression Nonparametric estimation Truncated density Classificació AMS::90 Operations research, mathematical programming Àrees temàtiques de la UPC::Matemàtiques i estadística::Investigació operativa |
| Resumo: | Two existing density estimators based on local likelihood have properties that are comparable to those of local likelihood regression but they are much less used than their counterparts in regression. We consider truncation as a natural way of localising parametric density estimation. Based on this idea, a third local likelihood density estimator is introduced. Our main result establishes that the three estimators coincide when a free multiplicative constant is used as an extra local parameter. |
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