Full Paper View Go Back

Efficient Hierarchic Multivariate Product-Based Estimator

K.B.Panda 1 , P.Das 2

  1. Department of Statistics, Utkal University, Bhubaneswar, India.
  2. Department of Statistics, Utkal University, Bhubaneswar, India.

Correspondence should be addressed to: prabhatadas91@gmail.com.


Section:Research Paper, Product Type: Isroset-Journal
Vol.5 , Issue.2 , pp.65-69, Apr-2018


CrossRef-DOI:   https://doi.org/10.26438/ijsrmss/v5i2.6569


Online published on Apr 30, 2018


Copyright © K.B.Panda, P.Das . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

View this paper at   Google Scholar | DPI Digital Library


XML View     PDF Download

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: K.B.Panda, P.Das, “Efficient Hierarchic Multivariate Product-Based Estimator,” International Journal of Scientific Research in Mathematical and Statistical Sciences, Vol.5, Issue.2, pp.65-69, 2018.

MLA Style Citation: K.B.Panda, P.Das "Efficient Hierarchic Multivariate Product-Based Estimator." International Journal of Scientific Research in Mathematical and Statistical Sciences 5.2 (2018): 65-69.

APA Style Citation: K.B.Panda, P.Das, (2018). Efficient Hierarchic Multivariate Product-Based Estimator. International Journal of Scientific Research in Mathematical and Statistical Sciences, 5(2), 65-69.

BibTex Style Citation:
@article{_2018,
author = {K.B.Panda, P.Das},
title = {Efficient Hierarchic Multivariate Product-Based Estimator},
journal = {International Journal of Scientific Research in Mathematical and Statistical Sciences},
issue_date = {4 2018},
volume = {5},
Issue = {2},
month = {4},
year = {2018},
issn = {2347-2693},
pages = {65-69},
url = {https://www.isroset.org/journal/IJSRMSS/full_paper_view.php?paper_id=580},
doi = {https://doi.org/10.26438/ijcse/v5i2.6569}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v5i2.6569}
UR - https://www.isroset.org/journal/IJSRMSS/full_paper_view.php?paper_id=580
TI - Efficient Hierarchic Multivariate Product-Based Estimator
T2 - International Journal of Scientific Research in Mathematical and Statistical Sciences
AU - K.B.Panda, P.Das
PY - 2018
DA - 2018/04/30
PB - IJCSE, Indore, INDIA
SP - 65-69
IS - 2
VL - 5
SN - 2347-2693
ER -

505 Views    269 Downloads    194 Downloads
  
  

Abstract :
We, in this paper, have proposed a multivariate product estimator using multi-auxiliary information. The performance of the proposed multivariate product-based estimator of order k, both under one-phase and two-phase sampling, is compared against the customary multivariate product estimator and the simple mean under conditions which hold good in practice very often. Moreover, the estimator is shown to be more efficient than the competing estimators invariably when k is determined optimally. The superiority of the estimator has been numerically illustrated by considering data from two real populations.

Key-Words / Index Term :
Hierarchic multivariate product-based estimator, auxiliary information, predictive estimation

References :
[1] M.C. Agrawal, K.B. Panda- Multivariate Product Estimators, Jour. Ind. Soc. Ag. Statistics, 45(3), 359-371, 1993.
[2] M.C. Agrawal, A. B. Sthapit- Hierarchic predictive ratio-based & product-based estimators and their efficiencies. Journal of Applied Statistics, Vol. 24, No. 1, 97- 104. 1997.
[3] D. Basu- An essay on the logical foundations of statistical inference, Part I, Foundations of Statistical Inference, Ed. By V.P. Godambe and D.A. Sportt, New York, 203-233, 1971.
[4] K.B. Panda- Some contributions to the Theory of Survey Sampling. Ph.D. thesis submitted to University of Delhi,Delhi-11007, 1994.
[4] T.M.F. Smith- The foundations of survey sampling, a review, Jour. R. Statist. -Soc., Series A, 139, 183-204, 1976.
[5] G.K. Vishwakarma, M. Kumar- An improved class of chain ratio-product type estimators in two-phase sampling using two auxiliary variables, Jour. of Prob. and Stat., Vol. 2014
[6] S. Weisberg,- Applied Linear Regression, John Wiley & Sons, Inc., New York, 1980.

Authorization Required

 

You do not have rights to view the full text article.
Please contact administration for subscription to Journal or individual article.
Mail us at  support@isroset.org or view contact page for more details.

Go to Navigation