On shrinkage least squares estimation in a parallelism problem

DOI10.1080/03610928608829195zbMath0611.62078OpenAlexW2008414448MaRDI QIDQ3750832

Pranab Kumar Sen, A. K. Md. Ehsanes Saleh

Publication date: 1986

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

Full work available at URL: https://doi.org/10.1080/03610928608829195

zbMATH Keywords

homogeneityinadmissibilityasymptotic distributional riskpreliminary test estimatorspreliminary test estimationregression slopesJames-Stein rulemulti-sample simple regression modelinterceptsparallelism problemshrinkage least squares estimators

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05) Nonparametric estimation (62G05)

Related Items (5)

Parameter Estimation when Various Models are Available ⋮ Preliminary test estimators and phi-divergence measures in generalized linear models with binary data ⋮ Improved nonparametric estimation of location vectors in multivariate regression models ⋮ Improved estimation in multiple linear regression models with measurement error and general constraint ⋮ Improved estimation of regression parameters in measurement error models

Cites Work

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• On some shrinkage estimators of multivariate location
• Nonparametric estimation of location parameter after a preliminary test on regression in the multivariate case
• On least squares estimation of intercepts after a preliminary test on parallelism of regression lines
• On a Class of Rank Order Tests for the Parallelism of Several Regression Lines
• Robust Statistical Procedures in Problems of Linear Regression with Special Reference to Quantitative Bio-Assays, I
• Non-Optimality of Preliminary-Test Estimators for the Mean of a Multivariate Normal Distribution

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