Stein type confidence interval of the disturbance variance in a linear regression model with multivariate student-t distributed errors

DOI10.1080/03610929708831930zbMath0900.62360OpenAlexW2091630453MaRDI QIDQ4337331

Yasushi Nagata

Publication date: 12 November 1998

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610929708831930

zbMATH Keywords

robustnesslinear modelcoverage probabilitypreliminary test estimationmultivariate Student-\(t\) distributiondisturbance varianceStein type estimator

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Parametric tolerance and confidence regions (62F25) Linear regression; mixed models (62J05)

Related Items (3)

Inconsistency of estimate of the degree of freedom of multivariate Student-\(t\) disturbances in linear regression models ⋮ Estimation of a scale parameter in mixture models with unknown location ⋮ Stein estimation -- a review

Cites Work

• Unnamed Item
• Estimation of error variance in linear regression models with errors having multivariate Student-\(t\) distribution with unknown degrees of freedom
• 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
• Estimating the error variance in regression after a preliminary test of restrictions on the coefficients
• Pre-testing for linear restrictions in a regression model with spherically symmetric disturbances
• Testing linear restrictions on coefficients in a linear regression model with proxy variables and spherically symmetric disturbances
• Inadmissibility of the usual estimator for the variance of a normal distribution with unknown mean
• On the Robustness of LM, LR, and W Tests in Regression Models
• Estimation of the parameters of a regression model with a multivariate t error variable
• JAMES-STEIN RULE ESTIMATORS IN LINEAR REGRESSION MODELS WITH MULTIVARIATE-t DISTRIBUTED ERROR
• Bayesian and Non-Bayesian Analysis of the Regression Model with Multivariate Student-t Error Terms
• The exact distribution and density functions of the stein-type estimator for normal variance
• The relationship between the improvement on the point estimation and the improvement on the interval estimation for the disturbance variance in a linear regression model
• The neyman accuracy and the wolfowitz accuracy of the stein type confidence interval for the disturbance variance

This page was built for publication: Stein type confidence interval of the disturbance variance in a linear regression model with multivariate student-t distributed errors