In this paper we consider a regression model and propose estimators which are the weighted averages of two estimators among three estimators; the Stein-rule (SR), minimum mean squared error (MMSE) and the adjusted minimum mean squared error (AMMSE) estimators. We derive the formula for the mean...

The estimation of the regression parameters for the ill-conditioned logistic regression model is considered in this paper. We proposed five ridge regression (RR) estimators, namely, unrestricted RR, restricted ridge regression, preliminary test RR, shrinkage ridge regression and positive rule RR...

This paper deals with the improved forecasts for the values of the study variable in linear regression models utilizing the minimum risk approach. It considers the simultaneous forecasting of actual and average values of the study variable and reports the performance properties of the classical...

The present paper uses small-sigma asymptotics to show that in general the shrinkage estimators have superior properties among the individual least squares estimators, the simple average estimators, the weighted average estimators, estimators obtained by shrinking towards the simple average, and...

The present paper uses small-sigma asymptotics to show that in general the shrinkage estimators have superior properties among the individual least squares estimators, the simple average estimators, the weighted average estimators, estimators obtained by shrinking towards the simple average, and...