Reduction of optimal calibration dimension with a new optimal auxiliary vector for calibrated estimators of the distribution function
The calibration method (Deville & Särndal, 1992) has been widely used to incorporate auxiliary information in the estimation of various parameters. Specifically, Rueda et al. (2007) adapted this method to estimate the distribution function, although their proposal is computationally simple, its...
| Main Authors: | , , |
|---|---|
| Format: | info:eu-repo/semantics/article |
| Language: | English |
| Published: |
2023
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/10835/14877 https://doi.org/10.1002/mma.8431 |
| _version_ | 1789406575044067328 |
|---|---|
| author | Martínez Puertas, Sergio Rueda García, María del Mar Illescas Manzano, María Dolores |
| author_facet | Martínez Puertas, Sergio Rueda García, María del Mar Illescas Manzano, María Dolores |
| author_sort | Martínez Puertas, Sergio |
| collection | DSpace |
| description | The calibration method (Deville & Särndal, 1992) has been widely used to incorporate auxiliary information in the estimation of various parameters. Specifically, Rueda et al. (2007) adapted this method to estimate the distribution function, although their proposal is computationally simple, its efficiency depends on the selection of an auxiliary vector of points. This work deals with the problem of selecting the calibration auxiliary vector that minimize the asymptotic variance of the calibration estimator of distribution function. The optimal dimension of the optimal auxiliary vector is reduced considerably with respect to previous studies (Martínez et al., 2017) so that with a smaller set of points the minimum of the asymptotic variance can be reached, which in turn allows to improve the efficiency of the estimates. |
| format | info:eu-repo/semantics/article |
| id | oai:repositorio.ual.es:10835-14877 |
| institution | Universidad de Cuenca |
| language | English |
| publishDate | 2023 |
| record_format | dspace |
| spelling | oai:repositorio.ual.es:10835-148772023-12-21T13:33:42Z Reduction of optimal calibration dimension with a new optimal auxiliary vector for calibrated estimators of the distribution function Martínez Puertas, Sergio Rueda García, María del Mar Illescas Manzano, María Dolores Survey sampling distribution function auxiliary information calibration The calibration method (Deville & Särndal, 1992) has been widely used to incorporate auxiliary information in the estimation of various parameters. Specifically, Rueda et al. (2007) adapted this method to estimate the distribution function, although their proposal is computationally simple, its efficiency depends on the selection of an auxiliary vector of points. This work deals with the problem of selecting the calibration auxiliary vector that minimize the asymptotic variance of the calibration estimator of distribution function. The optimal dimension of the optimal auxiliary vector is reduced considerably with respect to previous studies (Martínez et al., 2017) so that with a smaller set of points the minimum of the asymptotic variance can be reached, which in turn allows to improve the efficiency of the estimates. 2023-12-21T12:24:38Z 2023-12-21T12:24:38Z 2022-06-14 info:eu-repo/semantics/article 0170-4214 http://hdl.handle.net/10835/14877 https://doi.org/10.1002/mma.8431 en https://doi.org/10.1002/mma.8431 Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess |
| spellingShingle | Survey sampling distribution function auxiliary information calibration Martínez Puertas, Sergio Rueda García, María del Mar Illescas Manzano, María Dolores Reduction of optimal calibration dimension with a new optimal auxiliary vector for calibrated estimators of the distribution function |
| title | Reduction of optimal calibration dimension with a new optimal auxiliary vector for calibrated estimators of the distribution function |
| title_full | Reduction of optimal calibration dimension with a new optimal auxiliary vector for calibrated estimators of the distribution function |
| title_fullStr | Reduction of optimal calibration dimension with a new optimal auxiliary vector for calibrated estimators of the distribution function |
| title_full_unstemmed | Reduction of optimal calibration dimension with a new optimal auxiliary vector for calibrated estimators of the distribution function |
| title_short | Reduction of optimal calibration dimension with a new optimal auxiliary vector for calibrated estimators of the distribution function |
| title_sort | reduction of optimal calibration dimension with a new optimal auxiliary vector for calibrated estimators of the distribution function |
| topic | Survey sampling distribution function auxiliary information calibration |
| url | http://hdl.handle.net/10835/14877 https://doi.org/10.1002/mma.8431 |
| work_keys_str_mv | AT martinezpuertassergio reductionofoptimalcalibrationdimensionwithanewoptimalauxiliaryvectorforcalibratedestimatorsofthedistributionfunction AT ruedagarciamariadelmar reductionofoptimalcalibrationdimensionwithanewoptimalauxiliaryvectorforcalibratedestimatorsofthedistributionfunction AT illescasmanzanomariadolores reductionofoptimalcalibrationdimensionwithanewoptimalauxiliaryvectorforcalibratedestimatorsofthedistributionfunction |