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Housila P. Singh - One of the best experts on this subject based on the ideXlab platform.

  • a study on the chain ratio ratio type exponential estimator for finite Population Variance
    Communications in Statistics-theory and Methods, 2018
    Co-Authors: Housila P. Singh, Surya K. Pal, Anita Yadav
    Abstract:

    ABSTRACTThis paper considers the problem of estimating the Population Variance S2y of the study variable y using the auxiliary information in sample surveys. We have suggested the (i) chain ratio-type estimator (on the lines of Kadilar and Cingi (2003)), (ii) chain ratio-ratio-type exponential estimator and their generalized version [on the lines of Singh and Pal (2015)] and studied their properties under large sample approximation. Conditions are obtained under which the proposed estimators are more efficient than usual unbiased estimator s2y and Isaki (1893) ratio estimator. Improved version of the suggested class of estimators is also given along with its properties. An empirical study is carried out in support of the present study.

  • estimation of Population Variance using known coefficient of variation of an auxiliary variable in sample surveys
    Journal of Statistics and Management Systems, 2017
    Co-Authors: Housila P. Singh
    Abstract:

    AbstractThis paper addresses the problem of estimating the Population Variance of the study variable y using information on coefficient of variation Cx of an auxiliary variable x. We have suggested a class of estimators for the Population Variance. Expressions of bias and mean squared error of the proposed class of estimators are obtained under large sample approximation. It is identified that the usual unbiased estimator and Das and Tripathi’s (1978) estimators are members of the suggested class of estimators. It has been shown that proposed class of estimators is more efficient than usual unbiased estimator and Das and Tripathi’s (1978) estimators. An empirical study is given in support of the present study.

  • a family of estimators of Population Variance in two occasion rotation patterns
    Communications in Statistics-theory and Methods, 2016
    Co-Authors: Housila P. Singh, Jongmin Kim, Tanveer A Tarray
    Abstract:

    AbstractIn this article, we have considered the problem of estimation of Population Variance on current (second) occasion in two occasion successive (rotation) sampling. A class of estimators of Population Variance has been proposed and its asymptotic properties have been discussed. The proposed class of estimators is compared with the sample Variance estimator when there is no matching from the previous occasion and the Singh et al. (2013) estimator. Optimum replacement policy is discussed. It has been shown that the suggested estimator is more efficient than the Singh et al. (2013) estimator and a usual unbiased estimator when there is no matching. An empirical study is carried out in support of the present study.

  • Improved ratio-type estimators of finite Population Variance using quartiles
    Hacettepe Journal of Mathematics and Statistics, 2014
    Co-Authors: Housila P. Singh, Surya K. Pal, Ramkrishna S Solanki
    Abstract:

    In this paper we have proposed some ratio-type estimators of finite Population Variance using known values of parameters related to an auxiliary variable such as quartiles with their properties in simple random sampling. The suggested estimators have been compared with the usual unbiased and ratio estimators and the estimators due to [2], [12, 13, 14] and [3]. An empirical study is also carried out to judge the merits of the proposed estimator over other existing estimators of Population Variance using natural data set. 2000 AMS Classification: 62D05

  • a general procedure of estimating the Population Variance when coefficient of variation of an auxiliary variable is known in sample surveys
    Quality & Quantity, 2013
    Co-Authors: Rohini Yadav, Lakshmi N Upadhyaya, Housila P. Singh, S Chatterjee
    Abstract:

    This paper deals with the problem of estimating Population Variance \({{S}_{\rm y}^2}\) of the study variable y. We have suggested a family of estimators of Population Variance \({{S}_{\rm y}^2}\) using the transformations on both the study variable and the auxiliary variable when coefficient of variation of an auxiliary variable x is known. The suggested family of estimators is very wide from which we can generate many estimators by putting the suitable values of scalars. The bias and mean squared error have been obtained upto the first order of approximation. The empirical study is carried out to the support of the suggested family of estimators.

Sat Gupta - One of the best experts on this subject based on the ideXlab platform.

  • a note on generalized exponential type estimator for Population Variance in survey sampling
    Revista Colombiana de Estadistica, 2015
    Co-Authors: Javid Shabbir, Sat Gupta
    Abstract:

    Recently a new generalized estimator for Population Variance using information on the auxiliary variable has been introduced by Asghar, Sanaullah & 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.

  • improved family of estimators of Population Variance in simple random sampling
    Journal of statistical theory and practice, 2015
    Co-Authors: Subhash Kumar Yadav, Cem Kadilar, Javid Shabbir, Sat Gupta
    Abstract:

    In this article, we suggest a general procedure for estimating the Population Variance through a class of estimators. The bias and mean square error (MSE) of the proposed class of estimators are obtained to the first degree of approximation. The proposed class of estimators is more efficient than many other estimators, such as the usual Variance estimator, ratio estimator, the Bahal and Tuteja (1991) exponential estimator, the traditional regression estimator, the Rao (1991) estimator, the Upadhyaya and Singh (1999) estimator, and the Kadilar and Cingi (2006) estimators. Four data sets are used for numerical comparison.

  • Some Estimators of Finite Population Variance of Stratified Sample Mean
    Communications in Statistics - Theory and Methods, 2010
    Co-Authors: Javid Shabbir, Sat Gupta
    Abstract:

    This article proposes a ratio-type estimator for estimating the Variance of the stratified sample mean using auxiliary information. The proposed estimator is found to perform better than the usual unbiased Variance estimator, stratified ratio and regression estimators, and stratified version of Prasad and Singh (1992) estimator. We use five data sets to compare the performances of all of the estimators considered here.

  • Variance estimation in simple random sampling using auxiliary information
    Hacettepe Journal of Mathematics and Statistics, 2008
    Co-Authors: Sat Gupta, Javid Shabbir
    Abstract:

    In this paper we focus on investigating the precision of several Variance estimators considered by different authors, such as those suggested by Isaki (Variance estimation using auxiliary information, J. Amer. Stat. Assoc. 78, 117-123, 1983), and Kadilar and Cingi (Ratio estimators for Population Variance in simple and stratified sampling, Appl. Math. Comp. 173, 1047-1058 and Improvement in Variance estimation using auxiliary information, Hacet. J. Math. Stat. 35(1), 111-115, 2006). We propose a new hybrid class of estimators and show that in some cases their efficiency is better than the aforementioned traditional r and regression estimators of Isaki, and Kadilar and Cingi. Four nu- merical examples are considered to further evaluate the performance of these estimators.

  • on estimation of finite Population Variance
    Journal of Interdisciplinary Mathematics, 2006
    Co-Authors: Javid Shabbir, Sat Gupta
    Abstract:

    Abstract Following Searls (1964), we propose an estimator for estimating the finite Population Variance. This estimator is the combination of Singh et al. (1973), and Prasad and Singh (1992) estimators and has an improvement over Singh et al. (1973), Prasad and Singh (1992), and several other estimators under certain conditions. Validity of proposed estimator is examined by using seven numerical examples.

Bijaya Ketan Panigrahi - One of the best experts on this subject based on the ideXlab platform.

  • economic load dispatch using Population Variance harmony search algorithm
    Transactions of the Institute of Measurement and Control, 2012
    Co-Authors: Bijaya Ketan Panigrahi, Swagatam Das, Ravikumar V Pandi, Zhihua Cui, Renu Sharma
    Abstract:

    This paper presents a novel stochastic optimization approach to solve the constrained economic load dispatch (ELD) problem using the harmonic search algorithm (HS). HS is a recently developed derivative-free, meta-heuristic optimization algorithm, which draws inspiration from the musical process of searching for a perfect state of harmony. This work analyses the evolution of the Population-Variance over successive generations in HS and thereby draws some important conclusions regarding the explorative power of HS. The proposed methodology easily takes care of solving non-convex ELD problems along with different constraints like transmission losses, ramp rate limits of the generators and prohibited operating zones. Simulations were performed over various standard test systems with different number of generating units and a comparative study is carried out with other existing relevant approaches. The findings affirmed the robustness and proficiency of the proposed methodology over other existing techniques.

  • exploratory power of the harmony search algorithm analysis and improvements for global numerical optimization
    Systems Man and Cybernetics, 2011
    Co-Authors: Swagatam Das, Ajith Abraham, Arpan Mukhopadhyay, Ajit K Roy, Bijaya Ketan Panigrahi
    Abstract:

    The theoretical analysis of evolutionary algorithms is believed to be very important for understanding their internal search mechanism and thus to develop more efficient algorithms. This paper presents a simple mathematical analysis of the explorative search behavior of a recently developed metaheuristic algorithm called harmony search (HS). HS is a derivative-free real parameter optimization algorithm, and it draws inspiration from the musical improvisation process of searching for a perfect state of harmony. This paper analyzes the evolution of the Population-Variance over successive generations in HS and thereby draws some important conclusions regarding the explorative power of HS. A simple but very useful modification to the classical HS has been proposed in light of the mathematical analysis undertaken here. A comparison with the most recently published variants of HS and four other state-of-the-art optimization algorithms over 15 unconstrained and five constrained benchmark functions reflects the efficiency of the modified HS in terms of final accuracy, convergence speed, and robustness.

Mohd Khalid - One of the best experts on this subject based on the ideXlab platform.

  • effective estimation strategy of Population Variance in two phase successive sampling under random non response
    Journal of statistical theory and practice, 2019
    Co-Authors: G N Singh, Mohd Khalid
    Abstract:

    In this paper, an attempt has been made to present the problem of estimation of current Population Variance in the presence of random non-response in two-occasion successive sampling under two-phase setup. The properties of the proposed estimation procedures are deeply examined with the assumption that numbers of sampling units follow a distribution owing to random non-response. The performances of the proposed estimators are compared with the estimators designated for the complete response situations. We have discussed the effectiveness of the proposed estimators through the results that are interpreted by empirical studies. Appropriate recommendations have been made to the survey practitioners/researchers for their real-life practical applications.

Jongmin Kim - One of the best experts on this subject based on the ideXlab platform.

  • a family of estimators of Population Variance in two occasion rotation patterns
    Communications in Statistics-theory and Methods, 2016
    Co-Authors: Housila P. Singh, Jongmin Kim, Tanveer A Tarray
    Abstract:

    AbstractIn this article, we have considered the problem of estimation of Population Variance on current (second) occasion in two occasion successive (rotation) sampling. A class of estimators of Population Variance has been proposed and its asymptotic properties have been discussed. The proposed class of estimators is compared with the sample Variance estimator when there is no matching from the previous occasion and the Singh et al. (2013) estimator. Optimum replacement policy is discussed. It has been shown that the suggested estimator is more efficient than the Singh et al. (2013) estimator and a usual unbiased estimator when there is no matching. An empirical study is carried out in support of the present study.

  • a class of estimators for Population Variance in two occasion rotation patterns
    Communications for Statistical Applications and Methods, 2013
    Co-Authors: Geetanjali Singh, Sarjinder Singh, Priyanka Priyanka, Shakti Prasad, Jongmin Kim
    Abstract:

    A variety of practical problems can be addressed in the framework of rotation (successive) sampling. The present work presents a sample rotation pattern where sampling units are drawn on two successive occasions. The problem of estimation of Population Variance on current (second) occasion in two - occasion successive (rotation) sampling has been considered. A class of estimators has been proposed for Population Variance that includes many estimators as a particular case. Asymptotic properties of the proposed class of estimators are discussed. The proposed class of estimators is compared with the sample Variance estimator when there is no matching from the previous occasion. Optimum replacement policy is discussed. Results are supported with the empirical means of comparison.

  • families of estimators of finite Population Variance using a random non response in survey sampling
    The Korean Journal of Applied Statistics, 2012
    Co-Authors: Housila P. Singh, Rajesh Tailor, Jongmin Kim, Sarjinder Singh
    Abstract:

    In this paper, a family of estimators for the finite Population Variance investigated by Srivastava and Jhajj (1980) is studied under two different situations of random non-response considered by Tracy and Osahan (1994). Asymptotic expressions for the biases and mean squared errors of members of the proposed family are obtained; in addition, an asymptotic optimum estimator(AOE) is also identified. Estimators suggested by Singh and Joarder (1998) are shown to be members of the proposed family. A correction to the Singh and Joarder (1998) results is also presented.

  • estimation of Population Variance in successive sampling
    Quality & Quantity, 2011
    Co-Authors: Housila P. Singh, Ritesh Tailor, Sarjinder Singh, Jongmin Kim
    Abstract:

    This paper proposes a class of estimators of finite Population Variance in successive sampling on two occasions and analyzes its properties. Isaki (J Am Stat Assoc 78:117–123, 1983) motivated to consider the problem of estimation of finite Population Variance in survey sampling, and its extension to the case of successive sampling is much interesting, and the theory developed here will be helpful to those involved in such analysis in future. To our knowledge this is the first attempt made by the authors in this direction. An empirical study based on real Populations and moderate sample sizes demonstrates the usefulness of the proposed methodology. In addition, this paper also presents a through review on successive sampling.