Admissibility for linear estimators of regression coefficient in a general Gauss-Markoff model under balanced loss function
type: Item
instance of: scholarly article
title: Admissibility for linear estimators of regression coefficient in a general Gauss-Markoff model under balanced loss function
zbMATH Open document ID: 1207.62122
author: Guikai Hu
author: Ping Peng
published in: Journal of Statistical Planning and Inference
publication date: 2010-08-19T00:00:00Z
Mathematics Subject Classification ID: 62H12
Mathematics Subject Classification ID: 62C15
Mathematics Subject Classification ID: 62J05
zbMATH DE Number: 5773115
zbMATH Keywords: balanced loss function
zbMATH Keywords: linear estimators
zbMATH Keywords: admissibility
MaRDI profile type: Publication
full work available at URL: j.jspi.2010.05.004
OpenAlex ID: W2090525007
cites work: The exact risks of some pre-test and stein-type regression estimators umder balanced loss
cites work: The Efficiency of Shrinkage Estimators with Respect to Zellner's Balanced Loss Function
cites work: Improved prediction in the presence of multicollinearity
cites work: Ridge Regression: Biased Estimation for Nonorthogonal Problems
cites work: On estimation with weighted balanced-type loss function
cites work: The exact risk performance of a pre-test estimator in a heteroskedastic linear regression model under the balanced loss function
cites work: Q4381667
cites work: Inadmissibility of the Stein-rule estimator under the balanced loss function
cites work: Q5511769
cites work: Estimation of parameters in a linear model
cites work: Weighted balanced loss function and estimation of the mean time to failure
cites work: Q4749036
cites work: Q4761560
cites work: Q5461903
cites work: Q4284855
DOI: 10.1016/J.JSPI.2010.05.004
description: scientific article; zbMATH DE number 5773115