Follow
International Journal of Current Microbiology and Applied Sciences (IJCMAS)
IJCMAS is now DOI (CrossRef) registered Research Journal. The DOIs are assigned to all published IJCMAS Articles.
Index Copernicus ICI Journals Master List 2017 - IJCMAS--ICV 2017: 100.00 For more details click here
National Academy of Agricultural Sciences (NAAS) : NAAS Score: *5.38 (2019) [Effective from January 1, 2019]For more details click here

Login as a Reviewer

Indexed in



National Academy of Agricultural Sciences (NAAS)
NAAS Score: *5.38 (2019)
[Effective from January 1, 2019]
For more details click here

ICV 2017: 100.00
Index Copernicus ICI Journals Master List 2017 - IJCMAS--ICV 2017: 100.00
For more details click here

See Guidelines to Authors
Current Issues

Original Research Articles

PRINT ISSN : 2319-7692
Online ISSN : 2319-7706
Issues : 12 per year
Publisher : Excellent Publishers
Email : editorijcmas@gmail.com / submit@ijcmas.com
Editor-in-chief: Dr.M.Prakash
Index Copernicus ICV 2017: 100.00
NAAS RATING 2018: 5.38

Int.J.Curr.Microbiol.App.Sci.2018.7(10): 3358-3362
DOI: https://doi.org/10.20546/ijcmas.2018.710.389


Impact of Robust Estimators on Variance Estimation in Survey Sampling, Using Conventional and Non-Conventional Parameters as Auxiliary Information
M.A. Bhat*, T.A. Raja and S. Maqbool
Division of Agricultural Economics and Statist SKUAST-Kashmir (190025), India
*Corresponding author
Abstract:

In the present study, we have developed new estimators for the estimation of finite population variance by using auxiliary information as combination of conventional and non-conventional measures. Bias and mean square error has been worked out up to the first order of approximation. The empirical study has been carried out through numerical demonstration, under which improved estimators have performed better than the other existing estimators.


Keywords: Sample Random Sampling, Bias, MSE, Quartiles and efficiency
Download this article as Download

How to cite this article:

Bhat, M.A., T.A. Raja and Maqbool, S. 2018. Impact of Robust Estimators on Variance Estimation in Survey Sampling, Using Conventional and Non-Conventional Parameters as Auxiliary InformationInt.J.Curr.Microbiol.App.Sci. 7(10): 3358-3362. doi: https://doi.org/10.20546/ijcmas.2018.710.389