Shakti Prasad
@nitap.ac.in
Assistant Professor and Department of Basic & Applied Science
National Institute of Technology Arunachal Pradesh
RESEARCH, TEACHING, or OTHER INTERESTS
Statistics and Probability, Statistics, Probability and Uncertainty
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Vinay Kumar Yadav and Shakti Prasad
Informa UK Limited
Shakti Prasad and Vinay Kumar Yadav
Universidad Nacional de Colombia
Some efficient product type exponential imputation methods are proposed in this article to tackle the problem of incomplete values in sampling theory. To investigate the effectiveness of proposed exponential methods, the behaviours of the considered estimators are compared in two scenarios: with and without nonresponse. The simulation studies show that the proposed resultant estimators outperform other existing estimators in this literature.
Vinay Kumar Yadav and Shakti Prasad
Informa UK Limited
Shakti Prasad
Springer Science and Business Media LLC
Shakti Prasad
Polskie Towarzystwo Statystyczne
Abstract This paper deals some linear regression type ratio exponential estimators for estimating the population mean using the known values of quartile deviation and deciles of an auxiliary variable in survey sampling. The expressions of the bias and the mean square error of the suggested estimators have been derived. It was compared with the usual mean, usual ratio (Cochran (1977)), Kadilar and Cingi (2004, 2006) and Subzar et al. (2017) estimators. After comparison, the condition which makes the suggested estimators more efficient than others is found. To verify the theoretical results, numerical results are performed on two natural population data sets.
Shakti Prasad
Polskie Towarzystwo Statystyczne
Abstract In this paper, a product exponential method of imputation has been suggested and their corresponding resultant point estimator has been proposed for estimating the population mean in sample surveys. The expression of bias and the mean square error of the suggested estimator has also been derived, up to the first order of large sample approximations. Compared with the mean imputation method, Singh and Deo (Statistical Papers (2003)) and Adapted estimator (Bahl and Tuteja (1991)), the simulation studies show that the suggested estimator is the most efficient estimator.
Shakti Prasad
Hacettepe University
In this article, we have suggested new methods of ratio exponential type imputation and proposed their corresponding point estimators to deal with the problems of non-response in sample surveys for the prior outlay of an auxiliary variable $x$. The expression of the biases and their mean square errors of the proposed estimators have been derived, upto the fi rst order of large sample approximation under SRSWOR scheme and compared with the mean method of imputation, ratio method of impu tation, regression method of imputation and the estimators of Singh and Horn (Metrika [16]), Singh and Deo (Statistical Papers [15]), Touten burg et al. (Statistical Papers [18]), Singh (Statistics [17]) and Gira (Applied Mathematical Sciences [5]). After comparison, the condition which makes the proposed forty four estimators more efficient than others are found. To verify the theoretical results, simulation studies are performed on five real data sets.
Shakti Prasad
IOS Press
G. N. Singh and S. Prasad
Informa UK Limited
ABSTRACT In successive sampling some recent works depict the use of super-population models where information on stable auxiliary variable over occasions has been utilized. Stability character of auxiliary variable may not sustain, if the duration between occasions is large. To cope with such situations, the present work is an attempt to develop some estimation procedures by utilizing the information on two independent auxiliary variables through a linear super-population model. Some estimators are proposed to estimate the current population mean in two occasions successive (rotation) sampling. Optimum replacement strategies are formulated and performances of the proposed estimators have been discussed. Results are interpreted through empirical studies.
G. N. Singh, D. Majhi, S. Prasad, and F. Homa
Informa UK Limited
This article intends to develop some effective rotation patterns with the aid of attractive imputation methods when the problems of non response occur in two-occasion successive sampling. Utilizing the information on p (p ⩾ 1) auxiliary variables regression methods of imputation have been considered and subsequently multiple linear regression type estimators are proposed to estimate the current population mean in two-occasion successive sampling. Proposed estimators are compared with the estimator for same situations but in the absence of non-response. Optimum replacement strategies of the respective estimators have been discussed and results are interpreted with the help of empirical studies. Conclusions and suitable recommendations are made.
G.N. Singh, S. Prasad, and D. Majhi
IOS Press
G. N. Singh, V. K. Singh, Priyanka, Shakti Prasad, and Jaishree Prabha Karna
Informa UK Limited
The present article intends to develop some imputation methods to reduce the impact of non response at both the occasions in two-occasion successive (rotation) sampling. Utilizing the auxiliary information, which is only available at the current occasion, estimators have been proposed for estimating the population mean at the current occasion. Estimators for the current occasion are also derived as a particular case when there is non response either on the first occasion or second occasion. Behaviors of the proposed estimators are studied and their respective optimum replacement policies are also discussed. To study the effectiveness of the suggested imputation methods, performances of the proposed estimators are compared in two different situations, with and without non response. The results obtained are demonstrated with the help of empirical studies.
G. N. Singh, D. Majhi, and S. Prasad
IEEE
In the present work an attempt to estimate population mean on the current occasion using two-phase successive (rotation) sampling on two occasions has been made. Two-phase ratio, regression and regression-type estimators for estimating the population mean on current (second) occasion have been proposed. Optimum replacement policies of the proposed estimators have been discussed. The proposed estimator are compared with sample mean estimator when there is no matching and the optimum estimator which is a linear combination of the means of the matched and unmatched portions of the sample at the current occasion. Empirical studies are carried out and suitable recommendations are made.