Arnab Bandyopadhyay

Effectual Variance Estimation Strategy in Two Occasions Successive Sampling in Presence of Random Non-Response

ABSTRACT Present investigation deals with the problem of random non response in estimation of population variance on current occasion in two-occasion successive sampling. To reduce the negative impact of random non response on both occasions, regression type imputation method has been suggested. Using auxiliary information, efficient estimation strategies have been developed for estimation of population variance on the current occasion. Estimator for the population variance is also derived as a special case when random non response occurs only on the current occasion. Empirical studies are carried out to show the dominance of suggested estimators over sample variance and exponential type estimators. Results are interpreted.

Estimation of ratio of population means in two-occasion successive sampling

ABSTRACT This article considers the problem of estimation of the ratio of population means at the current occasion based on the samples selected over two occasions. Using auxiliary information on both the occasions, some classes of estimators have been proposed. Properties of the proposed estimators have been studied and their respective optimum replacement strategies are discussed. The gains in efficiency of the proposed classes of estimators over the direct estimator where no past information is used are computed. Theoretical results have been interpreted through empirical studies which are followed by suitable recommendations.

Estimation of Population Mean in Presence of Non Response in Two-Occasion Successive Sampling

The present work intended to emphasize the role of one varying auxiliary variable at both the occasions to improve the precision of estimates of population mean at current occasion in two-occasion successive sampling in presence of non-response. Two different efficient estimators are proposed and their theoretical properties are examined. The proposed estimators have been compared with (i) the sample mean estimator in the presence of non response, where no past information is used and (ii) the estimator suggested by Singh and Priyanka [1], which is a linear combination of the means of the matched and unmatched portions of the sample at the current occasion [1]. Theoretical results have been interpreted through empirical studies which are followed by suitable recommendations.

Effective Estimation of Ratio and Product of Two Population Means in Presence of Random Non-Response in Successive Sampling

The present article intends to develop efficient estimation strategy to reduce the negative impact of random non respon se at both occasions in two occasion successive sampling. Util izing the information on an auxiliary variable effective im putation strategy was developed to cope with the non -response situation. Esti mators for the current occasion are also derived as a particu l r ase when there is non-response either on the first occasion or on t he second occasion. To study the efficacy of the suggested imp utation method, performances of the proposed estimators are perfor med in two different situations: with and without non-respo nse. The preeminence of the suggested estimator has been established th rough empirical studies carried over some natural populati on dataset and artificially generated population dataset, which presents the soundness and usefulness of the suggested estimator in p ractice. Suitable recommendations to the survey statistician are also made.

Hunt for efficient variance estimation strategy in two-occasion successive sampling using fuzzy tools

Abstract The purpose of this paper is to report a general group of estimators for population variance estimation on second (current) occasion in two–occasion rotation sampling. Behaviors of the introduced class of estimators are studied in detail and its optimum replacement policy has also been observed. The introduced class of estimators has been compared with the natural estimator of the population variance and the results obtained are demonstrated empirically. The dominance ranges of the proposed estimation strategies are identified and illustrated through fuzzification tools followed by suitable recommendations.

Estimation of population mean in successive sampling under super-population model in presence of random non response situations

Abstract The present work is an attempt to estimate the population mean on the current occasion in two-occasion successive (rotation) sampling in presence of random non response situations. The estimation strategy has been constructed under a super-population model design approach with the help of imputation technique. The estimators proposed on the current occasion cover the cases of occurrences random non responses on either of the occasions. Detail behaviors of the proposed class of estimators have been studied and its performance has been examined with the sample mean estimator. The results are demonstrated through empirical studies which establish the effectiveness of the proposed class of estimators. Suitable recommendations have been put forward to the survey statisticians for its practical application.

Estimation of population mean in presence of random non response in two-stage cluster sampling

Abstract The present investigation addresses the problem of estimating a finite population mean in two-phase cluster sampling in presence of random non response situations. Utilizing information on an auxiliary variable, regression type estimators has been proposed. Effective imputation techniques have been suggested to deal with the random non response situations. The properties of the proposed estimation strategies have been studied for different cases of random non response situations in practical surveys. The superiority of the suggested methodology over the natural sample mean estimator of population mean has been established through empirical studies carried over the data sets of natural population and artificially generated population.

A Class of Exponential Regression Type Estimators for Population Variance in Two-Phase Sampling

This article deals with the problems of efficient estimation of population variance in two-phase (double) sampling. Using information on two auxiliary variables, a class of chain exponential to regression type estimators has been proposed and its properties are studied under two different structures of two-phase sampling. Superiority of suggested class of estimators over some existing ones is established through numerical illustrations. Suitable recommendations to the survey statistician are also made.

Predictive estimation of population mean in two-phase sampling

ABSTRACT The present investigation deals with the problem of estimation of population mean in two-phase sampling. In the presence of two auxiliary variables, some classes of estimators have been proposed through predictive approach. Properties of the proposed classes of estimators have been studied, and the unbiased versions of these estimators along with their approximate variance expressions are obtained under simple random sampling without replacement scheme. The respective optimum strategies of the proposed estimators are discussed, and their empirical and graphical comparisons with some contemporary estimators of population mean have been made. Suitable recommendations to the survey practitioner are given.