Prediction of Response Values in Linear Regression Models from Replicated Experiments

Toutenburg, Helge and Shalabh (1998): Prediction of Response Values in Linear Regression Models from Replicated Experiments. Collaborative Research Center 386, Discussion Paper 112

Abstract

This paper considers the problem of prediction in a linear regression model when data sets are available from replicated experiments. Pooling the data sets for the estimation of regression parameters, we present three predictors - one arising from the least squares method and two stemming from Stein-rule method. Efficiency properties of these predictors are discussed when they are used to predict actual and average values of response variable within/out-side the sample. Key words: least squares estimator, prediction, Stein-type estimator

• Item Type: Paper (Research Paper)
• Collections: Mathematics, Computer Science and Statistics > Statistics > Collaborative Research Center 386; Special Research Fields > Special Research Field 386
• Subjects: 500 Science > 510 Mathematics