@misc{10481/93166,
year = {2024},
month = {3},
url = {https://hdl.handle.net/10481/93166},
abstract = {The distribution function is a functional parameter of great interest in many research areas, such
as medicine or economics. Among other properties, it facilitates the estimation of parameters
such as quantiles. Accordingly, techniques are needed to estimate this function efficiently.
Survey statisticians have access to large, high-dimension databases and use them to optimise
the estimates obtained. One way to incorporate auxiliary information in the estimation stage
is through the calibration method, which was initially designed to estimate totals and means
and consists of adjusting new sample weights in order to reduce the variance of estimators.
However, calibration techniques may be subject to over-calibration, i.e. the loss of efficiency
when high-dimension auxiliary data sets are incorporated.
Although alternative approaches have been proposed, in which the calibration method incorporates
auxiliary information in the estimation of the distribution function, these alternatives do
not seek to incorporate qualitative auxiliary information, which must be introduced in the usual
way through dummy variables. However, this workaround can greatly increase the dimension
of the auxiliary information, producing either over-calibration or even incompatible calibration
constraints.
In this article, we propose adapting the calibration method through multidimensional
scaling, in order to incorporate quantitative and qualitative information, thus avoiding the
negative consequences of over-calibration in the estimation of the distribution function.},
organization = {PID2019-106861RB-I00 supported by MCIN/AEI/10.13039/501100011033, Spain},
organization = {CEX2020-001105-M supported by Consejería de Universidad, Investigación e Innovación},
organization = {ERDF Andalusia Program
2021-2027, Andalusia, Spain},
publisher = {Elsevier},
keywords = {Sampling},
keywords = {Distribution function},
keywords = {Calibration},
title = {Calibration estimation of distribution function based on multidimensional scaling of auxiliary information},
doi = {10.1016/j.cam.2024.115876},
author = {Martínez, Sergio and D. Illescas, María and Rueda García, María Del Mar},
}