Liu-type shrinkage estimations in linear models

Autor:	Bahadır Yüzbaşı, Yasin Asar, S. Ejaz Ahmed
Rok vydání:	2022
Předmět:	Statistics and Probability FOS: Mathematics Mathematics - Statistics Theory Statistics Theory (math.ST) Statistics Probability and Uncertainty
Zdroj:	Statistics. 56:396-420
ISSN:	1029-4910 0233-1888
DOI:	10.1080/02331888.2022.2055030
Popis:	In this study, we present the preliminary test, Stein-type and positive part Liu estimators in the linear models when the parameter vector $\boldsymbol{\beta}$ is partitioned into two parts, namely, the main effects $\boldsymbol{\beta}_1$ and the nuisance effects $\boldsymbol{\beta}_2$ such that $\boldsymbol{\beta}=\left(\boldsymbol{\beta}_1, \boldsymbol{\beta}_2 \right)$. We consider the case that a priori known or suspected set of the explanatory variables do not contribute to predict the response so that a sub-model may be enough for this purpose. Thus, the main interest is to estimate $\boldsymbol{\beta}_1$ when $\boldsymbol{\beta}_2$ is close to zero. Therefore, we conduct a Monte Carlo simulation study to evaluate the relative efficiency of the suggested estimators, where we demonstrate the superiority of the proposed estimators.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b874747fdcb70d21058fd7a894ca92e1 https://doi.org/10.1080/02331888.2022.2055030 Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
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