Open Access Open Access  Restricted Access Subscription or Fee Access

Study of A One Parameter Class of Ratio Cum Product Type Compromised Imputation Technique in Survey Sampling

Upasana Gogoi, B.K. Singh

Abstract



In this paper, a one parameter class of ratio-cum-product type compromised imputation technique and corresponding point estimator has been proposed and also the expressions for bias and mean square error are derived. Further, empirical studies are given to compare the performance of the estimator with other existing estimators such as mean method of imputation, ratio method of imputation, compromised method of imputation and Ahmed methods of imputation. It has been found that the ratio-cum-product estimator is more efficient than other existing methods of imputation.

Keywords


Ratio cum product, simple random sampling, Mean square error (MSE), Bias, Efficiency.

Full Text:

PDF


Disclaimer/Regarding indexing issue:

We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information.