A class of linear models for a two-stage cluster sample is considered. The best linear unbiased predictor of the finite population total can be obtained through extended least squares under these models. The effort of computing the prediction variance of the predictor may be reduced.two-stage cluster sample prediction variance extended least squares model-based approach
Data heterogeneity, within a (linear) regression framework, often suggests the use of a Clusterwise ...
Two-stage sampling usually leads to higher variances for estimators of means andregression coecients...
PublicationEstimation of finite population parameters has been an area of concern to statisticians f...
This paper considers the problem of estimating the population total in two-stage cluster sampling wh...
Abstract: This paper considers the problem of estimating the population total in two-stage cluster ...
In many situations there is interest in parameters (e.g., mean) associated with the response distrib...
Prediction of random effects is an important problem with expanding applications. In the simplest co...
ABSTRACT In many situations there is interest in parameters (e.g. mean) associated with the response...
Prediction of random effects is an important problem with expanding applications. In the simplest co...
In this paper, a nonlinear model is proposed for improving the relationship between the size of a cl...
In multilevel populations, there are two types of population means of an outcome variable ie, the av...
In regression analysis we make several assumptions about the error term. The following assumptions a...
Summary. The aims of this article are twofold: first estimate the parameters of the superpopulation ...
Estimating a predictive model from a dataset is best initiated with an unbiased estimator. However, ...
Two-stage sampling usually leads to higher variances for estimators of means and regression coeffici...
Data heterogeneity, within a (linear) regression framework, often suggests the use of a Clusterwise ...
Two-stage sampling usually leads to higher variances for estimators of means andregression coecients...
PublicationEstimation of finite population parameters has been an area of concern to statisticians f...
This paper considers the problem of estimating the population total in two-stage cluster sampling wh...
Abstract: This paper considers the problem of estimating the population total in two-stage cluster ...
In many situations there is interest in parameters (e.g., mean) associated with the response distrib...
Prediction of random effects is an important problem with expanding applications. In the simplest co...
ABSTRACT In many situations there is interest in parameters (e.g. mean) associated with the response...
Prediction of random effects is an important problem with expanding applications. In the simplest co...
In this paper, a nonlinear model is proposed for improving the relationship between the size of a cl...
In multilevel populations, there are two types of population means of an outcome variable ie, the av...
In regression analysis we make several assumptions about the error term. The following assumptions a...
Summary. The aims of this article are twofold: first estimate the parameters of the superpopulation ...
Estimating a predictive model from a dataset is best initiated with an unbiased estimator. However, ...
Two-stage sampling usually leads to higher variances for estimators of means and regression coeffici...
Data heterogeneity, within a (linear) regression framework, often suggests the use of a Clusterwise ...
Two-stage sampling usually leads to higher variances for estimators of means andregression coecients...
PublicationEstimation of finite population parameters has been an area of concern to statisticians f...
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