Comparisons of estimators for regression coefficient in a misspecified linear model with elliptically contoured errors
type: Item
instance of: scholarly article
title: Comparisons of estimators for regression coefficient in a misspecified linear model with elliptically contoured errors
zbMATH Open document ID: 1342.62121
author: Ping Peng
author: Guikai Hu
author: Muhua Ding
published in: Journal of the Korean Statistical Society
publication date: 2016-07-29T00:00:00Z
Mathematics Subject Classification ID: 62J07
Mathematics Subject Classification ID: 62F10
zbMATH DE Number: 6607827
zbMATH Keywords: comparisons of estimators
zbMATH Keywords: misspecified linear model
zbMATH Keywords: elliptically contoured distribution
MaRDI profile type: Publication
full work available at URL: j.jkss.2016.01.007
OpenAlex ID: W2276987682
cites work: Preliminary test and Stein estimations in simultaneous linear equations
cites work: Improved preliminary test and Stein-rule Liu estimators for the ill-conditioned elliptical linear regression model
cites work: On shrinkage estimators in matrix variate elliptical models
cites work: Estimation of parameters of parallelism model with elliptically distributed errors
cites work: Regression model with elliptically contoured errors
cites work: A Family of Minimax Estimators of the Mean of a Multivariate Normal Distribution
cites work: Estimation and decision for linear systems with elliptical random processes
cites work: Estimating the error variance in regression after a preliminary test of restrictions on the coefficients
cites work: Q3996150
cites work: The Minimum Mean Square Error Linear Estimator and Ridge Regression
cites work: Improved estimation of the disturbance variance in a linear regression model
cites work: Comparisons of variance estimators in a misspecified linear model with elliptically contoured errors
cites work: Q3185327
cites work: Q4178373
cites work: Improving the estimators of the parameters of a probit regression model: a ridge regression approach
cites work: PMSE PERFORMANCE OF THE BIASED ESTIMATORS IN A LINEAR REGRESSION MODEL WHEN RELEVANT REGRESSORS ARE OMITTED
cites work: Optimal levels of significance of a pre-test in estimating the disturbance variance after the pre-test for a linear hypothesis on coefficients in a linear regression
cites work: On an adjustment of degrees of freedom in the minimim mean squared error ertimator
cites work: Theory of Preliminary Test and Stein‐Type Estimation With Applications
cites work: On some ridge regression estimators: a nonparametric approach
cites work: Improved ridge regression estimators for the logistic regression model
cites work: Q3237829
cites work: Inadmissibility of the usual estimator for the variance of a normal distribution with unknown mean
cites work: Q5626055
cites work: The exact density and distribution functions of the inequality constrained and pre-test estimators
cites work: Further results on optimal critical values of pre‐test when estimating the regression error variance
cites work: Bayesian and Non-Bayesian Analysis of the Regression Model with Multivariate Student-t Error Terms
cites work: Estimating the error variance after a pre-test for an interval restriction on the coefficients
DOI: 10.1016/J.JKSS.2016.01.007
description: scientific article; zbMATH DE number 6607827