@inproceedings{4807ab190f3449d9809b0c1dfcba561c,
title = "Optimum estimation and marginal distributions",
abstract = "In this work we use the sub-vector associated to a marginal distribution, in the same way, as sufficient statistics in the Rao-Blackwell theorem in improving an unbiased estimator. If a given parameter is relevant only for a marginal distribution and there is a minimum variance estimator in a certain class (for instance, linear or quadratic) of unbiased estimators, derived from the corresponding sub-vector, our procedure leads to an equivalent optimum estimator derived from the full vector.",
keywords = "Full vector, Marginal distribution, Minimum variance umbiased estimator, Optimum estimator, Sub vector",
author = "Ferreira, {Sandra S.} and D{\'a}rio Ferreira and C{\'e}lia Nunes and Mexia, {Jo{\~a}o T.}",
note = "Publisher Copyright: {\textcopyright} 2022 Author(s).; 2020 National Conference on Advances in Applied Sciences and Mathematics, NCASM 2020 ; Conference date: 24-09-2020 Through 25-09-2020",
year = "2022",
month = may,
day = "9",
doi = "10.1063/5.0080665",
language = "English",
series = "AIP Conference Proceedings",
publisher = "AIP - American Institute of Physics",
editor = "Arun Upmanyu and Mohit KumarKakkar and Pankaj Kumar and Jasdev Bhatti",
booktitle = "National Conference on Advances in Applied Sciences and Mathematics, NCASM 2020",
address = "United States",
}