AbstractIn finite sampling it is widely believed that the probability sampling distribution is irrelevant for inference from a given sample. A super-population model in stratified sampling is investigated to show that the probability sampling distribution is relevant. It is proved that the traditional estimator of a linear combination of strata means, which is admissible and minimax when the vector of sample sizes is fu;ed, is inadmissible when the vector of sample sizes is random. Two alternative estimators are investigated. Based on analysis which is partly analytical and partly numerical, it appears that both of them are better than the traditional estimator
Use of ranks in unequal probability sampling is examined for sample selection, stratification as wel...
A special case of stratified samples is considered where each stratum has the same number of units a...
Not AvailableThe problem of estimation of finite population mean in the presence of the random respo...
AbstractIn finite sampling it is widely believed that the probability sampling distribution is irrel...
Abstract: In scientific applications, interest usually focuses on the “superpopula-tion ” parameters...
SUMMARY. This article considers simultaneous estimation of means from several strata un-der error-in...
The sampling strategy that couples probability proportional-to-size sampling with the GREG estimator...
Estimation of finite population means is considered when samples are collected using a stratified sa...
In this paper new exponential type estimators are suggested for estimating the population mean in st...
A proper analysis o f survey data requires that sampling design be taken into account, when conclusi...
In stratified sampling when only one unit is selected from each stratum, the estimation of variance ...
This paper considers the combined problem of allocation and stratification in order to minimise the ...
This paper considers the combined problem of allocation and stratification in order to minimise the ...
Khoshnevisan et al. (2007) proposed a general family of estimators for population mean using known v...
In this paper we have suggested some median based estimators in absence of the auxiliary information...
Use of ranks in unequal probability sampling is examined for sample selection, stratification as wel...
A special case of stratified samples is considered where each stratum has the same number of units a...
Not AvailableThe problem of estimation of finite population mean in the presence of the random respo...
AbstractIn finite sampling it is widely believed that the probability sampling distribution is irrel...
Abstract: In scientific applications, interest usually focuses on the “superpopula-tion ” parameters...
SUMMARY. This article considers simultaneous estimation of means from several strata un-der error-in...
The sampling strategy that couples probability proportional-to-size sampling with the GREG estimator...
Estimation of finite population means is considered when samples are collected using a stratified sa...
In this paper new exponential type estimators are suggested for estimating the population mean in st...
A proper analysis o f survey data requires that sampling design be taken into account, when conclusi...
In stratified sampling when only one unit is selected from each stratum, the estimation of variance ...
This paper considers the combined problem of allocation and stratification in order to minimise the ...
This paper considers the combined problem of allocation and stratification in order to minimise the ...
Khoshnevisan et al. (2007) proposed a general family of estimators for population mean using known v...
In this paper we have suggested some median based estimators in absence of the auxiliary information...
Use of ranks in unequal probability sampling is examined for sample selection, stratification as wel...
A special case of stratified samples is considered where each stratum has the same number of units a...
Not AvailableThe problem of estimation of finite population mean in the presence of the random respo...