Adjustment of the Auxiliary Variable(s) for Estimation of a Finite Population Mean

In this paper we have worked to weight and transform various estimators by Prasad (1986) and Lui (1991). We have introduced some ratio and ratio type estimators under weighting, transformation and model based approach, environment. We have introduced estimators efficient than estimators proposed by Chakrabarty (1979), Singh and Singh (1997), Singh (2002) and Singh et al. (2006).model based approach; percent relative efficiency; product estimator; ratio estimator; regression estimator; simple mean unit estimator

A family of ratio estimators for population mean in extreme ranked set sampling using two auxiliary variables

In this paper we have adopted the Khoshnevisan et al. (2007) family of estimators to extreme ranked set sampling (ERSS) using information on single and two auxiliary variables. Expressions for mean square error (MSE) of proposed estimators are derived to first order of approximation. Monte Carlo simulations and real data sets have been used to illustrate the method. The results indicate that the estimators under ERSS are more efficient as compared to estimators based on simple random sampling (SRS), when the underlying populations are symmetric.Peer Reviewe

An Alternative to Warner’s Randomized Response Model

A modification to Warner’s (1965) Randomized Response Model is suggested. The suggested model is more efficient than the original model

Logit Estimation Using Warner’s Randomized Response Model

A modified hidden logit estimation procedure is presented based on Warner (1965) randomized response model. Monte Carlo simulations explore the behavior of this estimator and compare its performance with the ordinary logits estimator. Warner’s model is more protective and less jeopardizing

Bayesian estimation of population proportion in Kim and Warde mixed randomized response technique

In this study, we have developed the Bayesian estimator of the population proportion of a sensitive characteristic when data are obtained through the Randomized Response Technique (RRT) proposed by Kim and Warde (2005). Superiority of the Bayesian estimators is established for a wide range of the values of the population proportion using simple Beta prior information.  It is observed that Bayesian estimators are better than the usual Maximum Likelihood Estimator (MLE) for small as well as moderate samples. The Proposed estimator is also compared with the Warner (1965), Kim and warde (2005) and Kim et al. (2006) estimators

A General Class Of Estimators For Finite Population Mean In The Presence Of Non-Response When Using The Second Raw Moments

In this paper, a general class of family of estimators for estimation of finite population mean is proposed under non-response, by using information on second raw moments. Properties of some ratio, product, modified ratio and modified product type estimators, which are members of a suggested class of estimators, are studied.  It is shown that a suggested class of estimators performs better than the usual ratio and product type estimators as well as regression and other considered estimators. A numerical study is carried out to support a suggested class of estimators

Hartley-Ross Type Unbiased Estimators Using Ranked Set Sampling and Stratified Ranked Set Sampling

This paper proposes several Hartley-Ross (HR) type unbiased estimators of the finite population mean using information on known population parameters of the auxiliary variable in ranked set sampling (RSS) and stratified ranked set sampling (StRSS). The variances of the proposed HR unbiased ratio-type estimators are obtained to first degree of approximation. In simulation study the proposed estimators are more efficient as compared to all other competitor estimators

Some Modified Exponential-Ratio Type Estimators in the presence of Non-response under Two-Phase Sampling Scheme

This paper addresses the problem of estimating the population mean using information on the auxiliary variable in the presence of non-response under two-phase sampling. A class of modified exponential-ratio type estimators using single auxiliary variable have been proposed under two different situations of non-response of the study variable. The expressions for the bias and mean square error (MSE) of a proposed class of estimators are derived. Efficiency comparisons of a proposed class of estimators with the usual unbiased estimator by Hansen and Hurwitz (1946) and other existing estimators are made. An empirical study has been carried out to judge the performances of the proposed estimators

Estimation of finite population mean by using minimum and maximum values in stratified random sampling

In this paper we have suggested an improved class of ratio type estimators in estimating the finite population mean when information on minimum and maximum values of the auxiliary variable is known. The properties of the suggested class of estimators in terms of bias and mean square error are obtained up to first order of approximation. Two data sets are used for efficiency comparisons

A Note on Generalized Exponential Type Estimator for Population Variance in Survey Sampling

Recently a new generalized estimator for population variance using information on the auxiliary variable has been introduced by Asghar, Sanaullah  and Hanif (2014). In that paper there was some inaccuracy in the bias and MSE expressions. In this paper, we provide the correct expressions for bias and MSE of the Asghar et al. (2014) estimator, up to the first order of approximation. We also propose a new generalized exponential type estimator for population variance which performs better than the existing estimators. Four data sets are used for numerical comparison of efficiencies.Recientemente, un nuevo estimador generalizado de varianza de la población utilizando información sobre la variable auxiliar ha sido introducida por Asghar et al. (2014). En ese documento había alguna inexactitud en las expresiones de sesgo y ECM. En este trabajo, proporcionamos las expresiones correctas de sesgo y ECM de Asghar et al. (2014) hasta el primer orden de aproximación. También proponemos un nuevo estimador tipo exponencial generalizado de la varianza de la población que se comporta mejor que los estimadores existentes. Cuatro conjuntos de datos se utilizan para la comparaciónnumérica de la eficiencia