Pre-test estimation and design in the linear model

DOI10.1016/0378-3758(96)00115-2zbMath0848.62037OpenAlexW1967812347MaRDI QIDQ1918232

Norbert Benda

Publication date: 27 October 1996

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0378-3758(96)00115-2

zbMATH Keywords

D-optimalitylinear modelpolynomial regressionquadratic losscontinuous designisotonic criterion function of the asymptotic risk matrixpre-test estimation functionrobust method against model deviation

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Optimal statistical designs (62K05)

Related Items (15)

Performance of the preliminary test two-parameter estimators based on the conflicting test statistics in a regression model with Student'sterror ⋮ Performance of the stein-type two-parameter estimator in multiple linear regression model ⋮ Preliminary test almost unbiased two-parameter estimators with student’sterrors and conflicting test statistics ⋮ Preliminary Test Estimators Induced by Three Large Sample Tests for Stochastic Constraints in a Regression Model with Multivariate Student-t Error ⋮ Improved preliminary test and Stein-rule Liu estimators for the ill-conditioned elliptical linear regression model ⋮ Preliminary test estimation of the parameters of exponential and Pareto distributions for censored samples ⋮ On preliminary test almost unbiased two-parameter estimator in linear regression model with student's t errors ⋮ Some Liu and ridge-type estimators and their properties under the ill-conditioned Gaussian linear regression model ⋮ On shrinkage estimators in matrix variate elliptical models ⋮ Improved ridge regression estimators for the logistic regression model ⋮ براوردگر پیش آزمون در مدل نمایی دو پارامتری تحت سانسور فزاینده نوع دوم ⋮ Optimum Critical Value for Pre-Test Estimator ⋮ On Liu-type biased estimators in measurement error models ⋮ On some ridge regression estimators: a nonparametric approach ⋮ A two-stage strategy for the construction of d-optimal experimental designs

Cites Work

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• Pre-testing in a mis-specified regression model
• Contamination in linear regression models and its influence on estimators
• A study of the equivalence between a gauss-markoff model and its augmentation by nuisance parameters
• Duality of optimal designs for model discrimination and parameter estimation
• Robust estimation of the mean of the exponential distribution in outlier situations
• The design of experiments for discriminating between two rival models
• The Statistical Consequences of Preliminary Test Estimators in Regression

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