Necessary and su cient conditions for the equality of ordinary least squares and generalized least squares estimators in the linear regression model with rst order spatial error processes are given

For a random e ects regression model with unbalanced panel data, we demonstrate that the Generalized Least Squares (GLS) estimator can be expressed as a (matrix) weighted average of estimators which utilize the within individual and the between individual variation in the data set. We thus generalize a relationship familiar for balanced panel data. Speci c attention must be given to the interce...

In this paper, possible solutions of problem of non-response in the variable of interest are proposed when information about an auxiliary attribute is available. By taking motivation from the previous work, modified classes have been suggested for estimating population mean. Two new generalized classes of estimators are presented along with their asymptotic biases and variances. Efficacy analys...

In Generalized Linear Models, likelihood equations are intractable and do not have explicit solutions; thus, they must be solved by using Newton-type algorithms. Solving these equations by iterations, however, can be problematic: the iterations might converge to wrong values or the iterations might not converge at all. In this study, we derive the modified maximum likelihood estimators for Pois...

In Generalized Linear Models, likelihood equations are intractable and do not have explicit solutions; thus, they must be solved by using Newton-type algorithms. Solving these equations by iterations, however, can be problematic: the iterations might converge to wrong values or the iterations might not converge at all. In this study, we derive the modified maximum likelihood estimators for Pois...

Generalized chain ratio regression and chain regression estimators for the population mean using two auxiliary characters have been proposed in the presence of non-response. The expressions for the mean square error (MSE) of these estimators have been obtained for fixed sample sizes ( n′ and n ) and also for fixed cost 0 C C ≤ .The optimum values of the first phase sample size n′ and the sub sa...

In the context of ridge regression, the estimation of ridge (shrinkage) parameter plays an important role in analyzing data. Many efforts have been put to develop skills and methods of computing shrinkage estimators for different full-parametric ridge regression approaches, using eigenvalues. However, the estimation of shrinkage parameter is neglected for semiparametric regression models. The m...

A unified framework to deal with the effective use of complete auxiliary information from survey data at the estimation stage has been attempted. The proposed method involves modeling the relationship between the variable of interest and the auxiliary variables, and then incorporating the auxiliary information into design-consistent estimators of finite population means, totals, distribution fu...

In this article, we propose generalized two-parameter (GTP) estimators and an algorithm for the estimation of shrinkage parameters to combat multicollinearity in multinomial logit regression model. addition, mean squared error properties are derived. A simulation study is conducted investigate performance proposed different sample sizes, degrees multicollinearity, number explanatory variables. ...