Distribution function estimation with calibration on principal components
The calibration method is a convenient means of incorporating auxiliary information when several parameters must be estimated. This approach has recently been used to develop new estimators for the distribution function. However, the auxiliary information available may generate a large dataset, prov...
| Principais autores: | , , |
|---|---|
| Formato: | info:eu-repo/semantics/article |
| Idioma: | English |
| Publicado em: |
2023
|
| Acesso em linha: | http://hdl.handle.net/10835/14845 https://doi.org/10.1016/j.cam.2023.115189 |
| _version_ | 1789406658440462336 |
|---|---|
| author | Martínez Puertas, Sergio Illescas Manzano, María Dolores Rueda García, María del Mar |
| author_facet | Martínez Puertas, Sergio Illescas Manzano, María Dolores Rueda García, María del Mar |
| author_sort | Martínez Puertas, Sergio |
| collection | DSpace |
| description | The calibration method is a convenient means of incorporating auxiliary information when several parameters must be estimated. This approach has recently been used to develop new estimators for the distribution function. However, the auxiliary information available may generate a large dataset, provoking a loss of efficiency in the estimators obtained, due to over-calibration. We propose adapting the calibration using principal components, in order to avoid the negative consequences of over-calibration when estimating the distribution function. |
| format | info:eu-repo/semantics/article |
| id | oai:repositorio.ual.es:10835-14845 |
| institution | Universidad de Cuenca |
| language | English |
| publishDate | 2023 |
| record_format | dspace |
| spelling | oai:repositorio.ual.es:10835-148452023-12-21T13:36:42Z Distribution function estimation with calibration on principal components Martínez Puertas, Sergio Illescas Manzano, María Dolores Rueda García, María del Mar The calibration method is a convenient means of incorporating auxiliary information when several parameters must be estimated. This approach has recently been used to develop new estimators for the distribution function. However, the auxiliary information available may generate a large dataset, provoking a loss of efficiency in the estimators obtained, due to over-calibration. We propose adapting the calibration using principal components, in order to avoid the negative consequences of over-calibration when estimating the distribution function. 2023-12-19T09:35:19Z 2023-12-19T09:35:19Z 2023-11-03 info:eu-repo/semantics/article 1879-1778 http://hdl.handle.net/10835/14845 https://doi.org/10.1016/j.cam.2023.115189 en https://doi.org/10.1016/j.cam.2023.115189 Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess |
| spellingShingle | Martínez Puertas, Sergio Illescas Manzano, María Dolores Rueda García, María del Mar Distribution function estimation with calibration on principal components |
| title | Distribution function estimation with calibration on principal components |
| title_full | Distribution function estimation with calibration on principal components |
| title_fullStr | Distribution function estimation with calibration on principal components |
| title_full_unstemmed | Distribution function estimation with calibration on principal components |
| title_short | Distribution function estimation with calibration on principal components |
| title_sort | distribution function estimation with calibration on principal components |
| url | http://hdl.handle.net/10835/14845 https://doi.org/10.1016/j.cam.2023.115189 |
| work_keys_str_mv | AT martinezpuertassergio distributionfunctionestimationwithcalibrationonprincipalcomponents AT illescasmanzanomariadolores distributionfunctionestimationwithcalibrationonprincipalcomponents AT ruedagarciamariadelmar distributionfunctionestimationwithcalibrationonprincipalcomponents |