@misc{10481/87440,
year = {2023},
url = {https://hdl.handle.net/10481/87440},
abstract = {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 e ciency 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.},
organization = {Grant A-FQM-170-UGR20 supported by Consejería de Universidad, Investigaci
ón e Innovación de la Junta de Andalucía and FEDER.
Grant PID2019-106861RB-I00 supported by MCIN/ AEI /10.13039/501100011033
Grant CEX2020-001105-M supported by MCIN/AEI /10.13039/501100011033},
keywords = {Auxiliary information},
keywords = {distribution function},
keywords = {calibration technique},
keywords = {principal components},
keywords = {principal components},
title = {Distribution function estimation with calibration on principal components},
doi = {10.1016/j.cam.2023.115189},
author = {Martínez, Sergio and Illescas, María and Rueda García, María Del Mar},
}