Author
Housila P. Singh
Bio: Housila P. Singh is an academic researcher from Vikram University. The author has contributed to research in topics: Estimator & Mean squared error. The author has an hindex of 19, co-authored 225 publications receiving 1651 citations.
Papers published on a yearly basis
Papers
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TL;DR: In this paper, a class of estimators of the population variance using auxiliary information has been proposed, and the bias and mean squared errors of the suggested estimators upto the terms of order n − 1, and also optimum estimators in asymptotic sense of the class with approximate mean squared error formula.
Abstract: This article addresses the problem of estimating the population variance using auxiliary information in the presence of measurement errors. When the measurement error variance associated with study variable is known, a class of estimators of the population variance using auxiliary information has been proposed. We obtain the bias and mean squared errors of the suggested class of estimators upto the terms of order n −1, and also optimum estimators in asymptotic sense of the class with approximate mean squared error formula.
64 citations
TL;DR: In this paper, the problem of estimating the population mean of the study variable y using information on two auxiliary variables x and z in presence of nonresponse has been addressed and two classes of combined regression and ratio estimators are defined in two different situations along with their properties.
Abstract: This article addresses the problem of estimating the population mean of the study variable y using information on two auxiliary variables x and z in presence of nonresponse. Two classes of combined regression and ratio estimators are defined in two different situations along with their properties. An empirical study is carried out to judge the merits of the suggested estimators over usual unbiased estimator, ratio estimator and regression estimators. Both theoretical and empirical results are encouraging.
46 citations
TL;DR: In this paper, the problem of estimating population mean on the current (second) occasion using auxiliary information in successive sampling over two occasions is considered, and a class of estimators is defined with its properties.
Abstract: This article considers the problem of estimating population mean on the current (second) occasion using auxiliary information in successive sampling over two occasions. A class of estimators is defined with its properties. It is shown that the estimator envisaged by Singh (2005) is a particular member of the proposed class of estimators. The superiority of the suggested class of estimators is discussed with sample mean estimator when there is no matching, the best combined estimator given in Cochran (1977, p. 346), Sukhatme et al. (1984, p. 249), Singh's (2005) estimator, and Singh and Vishwakarma's (2007) class of estimators. Optimum replacement policy has been discussed. Numerical illustration is also given.
44 citations
TL;DR: In this paper, an alternative stratified randomized response model based on the model of Singh and Joarder (1997) is proposed, which is shown numerically to be more efficient than Hong et al. (1994) and Kim and Warde (2004) under optimum allocation.
Abstract: This paper proposes an alternative stratified randomized response model based on the model of Singh and Joarder (1997). It is shown numerically that the proposed stratified randomized response model is more efficient than Hong et al. (1994) (under proportional allocation ) and Kim and Warde (2004) (under optimum allocation).
43 citations
TL;DR: In this article, a class of ratio-product estimators in two-phase sampling with its properties is proposed and the asymptotically optimum estimators (AOEs) in the class are identified in two different cases with their variances.
Abstract: It is well known that two-phase (or double) sampling is of significant use in practice when the population parameter(s) (say, population mean X¯) of the auxiliary variate x is not known Keeping this in view, we have suggested a class of ratio-product estimators in two-phase sampling with its properties The asymptotically optimum estimators (AOEs) in the class are identified in two different cases with their variances Conditions for the proposed estimator to be more efficient than the two-phase sampling ratio, product and mean per unit estimator are investigated Comparison with single phase sampling is also discussed An empirical study is carried out to demonstrate the efficiency of the suggested estimator over conventional estimators
42 citations
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TL;DR: In his seminal book, Shewhart (1931) makes no demand on the distribution of the characteristic to be plotted on a control chart, so how can the idea that normality is, if not required, at least highly desirable be explained?
Abstract: In his seminal book, Shewhart (1931) makes no demand on the distribution of the characteristic to be plotted on a control chart. How then can we explain the idea that normality is, if not required, at least highly desirable? I believe that it has come about through the many statistical studies of control-chart behavior. If one is to study how a control chart behaves, it is necessary to relate it to some distribution. The obvious choice is the normal distribution because of its ubiquity as a satisfactory model. This is bolstered by the existence of the Central Limit Theorem.
896 citations
TL;DR: In this article, the authors introduce the concept of variance estimation and introduce the Variance Estimation Estimation Method (VEM) as an alternative to variance estimation for variance estimation.
Abstract: (2008). Introduction to Variance Estimation. Journal of the American Statistical Association: Vol. 103, No. 483, pp. 1324-1325.
562 citations
Journal Article•
162 citations
TL;DR: Pandurang V. Sukhatme as discussed by the authors, Sampling Theory of Surveys with Applications. Food and Agriculture Organisation of United Nations. 1954. Iowa State College Press and Indian Society of Agricultural Statistics.
Abstract: Pandurang V. Sukhatme: Sampling Theory of Surveys with Applications. Food and Agriculture Organisation of United Nations. Iowa State College Press and Indian Society of Agricultural Statistics. 1954. Pp. xxxi + 491. Rs. 25 or US $5.50.
152 citations
129 citations