Upper Bound of the Generalized p

This paper presents an upper bound for each of the generalized p values for testing the one population variance, the difference between two population variances, and the ratio of population variances for lognormal distribution when coefficients of variation are known. For each of the proposed generalized p values, we derive a closed form expression of the upper bound of the generalized p value. Numerical computations illustrate the theoretical results

A Ratio-cum-Dual to Ratio Estimator of Population Variance Using Qualitative Auxiliary Information Under Simple Random Sampling

In this paper we have proposed a class of ratio-cum-dual to ratio estimators for estimating population variance of the variable under study, using known values of some population parameters of auxiliary variable, which is available in the form of an attribute. The expressions for the bias and mean squared error of the proposed estimators have been derived up to the first order of approximation. A comparison has been made with some well-known estimators of population variance available in the literature when auxiliary information is in qualitative form. It has been shown that the proposed estimator is better than the existing estimators under the optimum condition. For illustration, an empirical study has been carried out

On the estimation of population variance using auxiliary attribute in absence and presence of non-response

In this article we proposed a new class of estimators for estimating thefinite population variance using available auxiliary attribute in absence and presence of non-response problem. Properties such as bias and mean square error of the proposed class are derived up to the first order of approximation. The proposed class is more efficient than the Singh et al. (1988), Shabbir and Gupta (2007), Singh and Solanki (2013a), usual sample variance and regression estimators

A NEW FAMILY OF ESTIMATORS OF THE POPULATION VARIANCE USING INFORMATION ON POPULATION VARIANCE OF AUXILIARY VARIABLE IN SAMPLE SURVEYS

This paper proposes a family of estimators of population variance 2 y S of the study variable y in the presence of known population variance 2 x S of the auxiliary variable x. It is identified that in addition to many, the recently proposed classes of estimators due to Sharma and Singh (2014) and Singh and Pal (2016) are members of the proposed family of estimators. Asymptotic expressions of bias and mean squared error (MSE) of the suggested family of estimators have been obtained. Asymptotic optimum estimator (AOE) in the family of estimators is identified. Some subclasses of estimators of the proposed family of estimators have been identified along with their properties. We have also given the theoretical comparisons among the estimators discussed in this paper. ASM Classification: 62D05

AUXILIARY INFORMATION AND A PRIORI VALUES IN CONSTRUCTION OF IMPROVED ESTIMATORS

This volume is a collection of six papers on the use of auxiliary information and a priori values in construction of improved estimators. The work included here will be of immense application for researchers and students who employ auxiliary information in any form. Below we discuss each paper: 1. Ratio estimators in simple random sampling using information on auxiliary attribute. Prior knowledge about population mean along with coefficient of variation of the population of an auxiliary variable is known to be very useful particularly when the ratio, product and regression estimators are used for estimation of population mean of a variable of interest. However, the fact that the known population proportion of an attribute also provides similar type of information has not drawn as much attention. In fact, such prior knowledge can also be very useful when a relation between the presence (or absence) of an attribute and the value of a variable, known as point biserial correlation, is observed. Taking into consideration the point biserial correlation between a variable and an attribute, Naik and Gupta (1996) defined ratio, product and regression estimators of population mean when the prior information of population proportion of units, possessing the same attribute is available. In the present paper, some ratio estimators for estimating the population mean of the variable under study, which make use of information regarding the population proportion possessing certain attribute are proposed. The expressions of bias and mean squared error (MSE) have been obtained. The results obtained have been illustrated numerically by taking some empirical populations considered in the literature