The present investigation deals with the problem of estimation of population variance in presence of random non-response in two-phase (double) sampling. Using information on two auxiliary variables, two general classes of estimators have been suggested in two different situations of random non-response and studied their properties under two different set up of two-phase sampling. It is shown that several estimators may be generated from our proposed classes of estimators. Proposed classes of estimators are empirically compared with some contemporary estimators of population variance under the similar realistic situations and their performances have been demonstrated through numerical illustration and graphical interpretation which are follo...
This paper deals with the estimation of current population mean under non-response in two-occasion s...
Kim and Yu (2011) discussed replication variance estimator for two-phase stratified sampling. In thi...
Population mean, Study variate, Auxiliary variate, Double sampling, Bias, Variance,
The present investigation deals with the problem of estimation of population variance in presence of...
In the present study, we propose a general class of estimators for population mean of the study vari...
The work done in this article is concerned with the development and efficient estimation procedure of...
An improved class of two phase sampling estimators for population mean using auxiliary character in ...
The present paper focuses on the use of double sampling scheme in stratified random sampling for est...
A general class of estimators for finite population variance is proposed under a two-phase sampling ...
This work is designed to assess the effect of non-response in estimation of the current population m...
This paper discusses estimation of the population total in double sampling for stratification in the...
This article deals with the problems of efficient estimation of population variance in two-phase (do...
Not AvailableThe estimation of population mean in the presence of non-response has been considered w...
In this paper, we have proposed some ratio-cum-product type estimators for population mean of the st...
This paper deals with the estimation of current population mean under non-response in two-occasion s...
This paper deals with the estimation of current population mean under non-response in two-occasion s...
Kim and Yu (2011) discussed replication variance estimator for two-phase stratified sampling. In thi...
Population mean, Study variate, Auxiliary variate, Double sampling, Bias, Variance,
The present investigation deals with the problem of estimation of population variance in presence of...
In the present study, we propose a general class of estimators for population mean of the study vari...
The work done in this article is concerned with the development and efficient estimation procedure of...
An improved class of two phase sampling estimators for population mean using auxiliary character in ...
The present paper focuses on the use of double sampling scheme in stratified random sampling for est...
A general class of estimators for finite population variance is proposed under a two-phase sampling ...
This work is designed to assess the effect of non-response in estimation of the current population m...
This paper discusses estimation of the population total in double sampling for stratification in the...
This article deals with the problems of efficient estimation of population variance in two-phase (do...
Not AvailableThe estimation of population mean in the presence of non-response has been considered w...
In this paper, we have proposed some ratio-cum-product type estimators for population mean of the st...
This paper deals with the estimation of current population mean under non-response in two-occasion s...
This paper deals with the estimation of current population mean under non-response in two-occasion s...
Kim and Yu (2011) discussed replication variance estimator for two-phase stratified sampling. In thi...
Population mean, Study variate, Auxiliary variate, Double sampling, Bias, Variance,