Linear minimax prediction of finite population regression coefficient under a balanced loss function

DOI10.1080/03610926.2014.978945zbMath1351.62176OpenAlexW2413847614MaRDI QIDQ2834721

Guikai Hu, Sheng-Hua Yu, Qing-Guo Li

Publication date: 23 November 2016

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

Full work available at URL: https://doi.org/10.1080/03610926.2014.978945

zbMATH Keywords

balanced loss functionfinite population regression coefficientlinear minimax predictor

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Admissibility in statistical decision theory (62C15)

Cites Work

• Bayes and minimax prediction in finite populations
• The linear minimax estimator of stochastic regression coefficients and parameters under quadrat\-ic loss function
• PMSE performance of the Stein-rule and positive-part Stein-rule estimators in a regression model with or without proxy variables
• Bayes Prediction for a Stratified Regression Superpopulation Model Using Balanced Loss Function
• Comparison of Two Estimators of Parameters Under Pitman Nearness Criterion
• ON THE SIMPLE PROJECTION PREDICTOR IN FINITE POPULATIONS
• Bayes Prediction for a Heteroscedastic Regression Superpopulation Model Using Balanced Loss Function
• Linearized Restricted Ridge Regression Estimator in Linear Regression

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