An Efficient Class of Exponential Chain Ratio Type Estimator for Finite Population Mean in Double Sampling

Diganta Kalita

doi:doi:10.11648/j.sjams.20150306.17

| Peer-Reviewed

An Efficient Class of Exponential Chain Ratio Type Estimator for Finite Population Mean in Double Sampling

Diganta Kalita

Published in Science Journal of Applied Mathematics and Statistics (Volume 3, Issue 6)

Received: 12 October 2015 Accepted: 4 November 2015 Published: 25 December 2015

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

This paper presents a class of exponential chain ratio type estimator in double sampling for estimating finite population mean of the study variable, when the information on another additional auxiliary variable is known along with the main auxiliary variable. The property of proposed class of estimator has been studied. Comparison has been made with other competitive estimators. The proposed estimator is found to be more efficient both theoretically and empirically.

Published in	Science Journal of Applied Mathematics and Statistics (Volume 3, Issue 6)
DOI	10.11648/j.sjams.20150306.17
Page(s)	281-287
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2015. Published by Science Publishing Group

Keywords

Auxiliary Character, Chaining in Double Sampling, Exponential Chain Ratio Type Estimator, Study Variable, MSE and Efficiency

References

[1]	Al-Jararha, J. & Ahmed, M. S. (2002). The class of chain estimators for a finite population variance using double sampling. Information and Management Sciences, 13(2), 13–18.
[2]	Amin, M. & Hanif, M. (2012). Some exponential estimators in survey sampling. Pak. J. Statist. 28(3), 67-374.
[3]	Bahl, S. &Tuteja, R. K. (1991). Ratio and Product type exponential estimator. Information and Optimization Sciences, 12, 159-163.
[4]	Chand, L. (1975). Some ratio type estimator based on two or more auxiliary variables. Unpublished Ph. D. dissertation, Lowa State University, Ames, Lowa.
[5]	Cochran, W. G. (1940). The estimation of the yields of the cereal experiments by sampling for the ratio of grain to total produce. The Journal of Agricultural Science, 30(2), 262–275.
[6]	Cochran, W. G. (1977). Sampling techniques. New-York: John Wiley and Sons.
[7]	J. Neyman. (1938). Contribution to the theory of sampling human populations. Journal of the American Statistical Association, (33), 101–116.
[8]	Kalita, et al. (2013). Improved exponential chain ratio and Product type Estimators for finite Population mean in double sampling. International Journal of Statistical Sciences, 13, 21-27.
[9]	Kiregyera, B. (1980). A chain ratio-type estimator in finite population in double sampling using two auxiliary variables. Metrika, 27, 217–223.
[10]	Murthy, M. N. (1967). Sampling theory and Methods. Calcutta, India: Statistical Publishing Soc.
[11]	Pradhan, B. K. (2005). A Chain Regression Estimator in Two Phase Sampling Using Multiauxiliary Information. Bulletin of the Malaysian Mathematical Sciences Society (2), 28(1), 81–86.
[12]	Singh, B.K. & Choudhury. S, (2012). Exponential chain ratio and product type estimators for finite population mean under double sampling scheme, Global Journal of Science Frontier Research, 12(6), 13-24.
[13]	Singh, H. P. & Vishwakarma, G. K. (2007). Modified exponential ratio and product estimators for finite population mean in double sampling. Austrian Journal of Statistics, 36(3), 217-225.
[14]	Srivastava, S. K. & Jhajj, H. S. (1980). A class of estimators using auxiliary information for estimating finite population variance. Sankhyā C, 42(1–2), 87–96.
[15]	Srivastava, et.al (1989). Chain ratio type estimator for ratio of two population means using auxiliary characters. Communications in Statistics –Theory and Methods, 18(10), 3917-3926.
[16]	Sukhatme, B. V. & Chand, L. (1977). Multivariate ratio-type estimators, Proceedings of American Statistical Association, Social Statistics Section, 927–931.
[17]	Sukhatme, B. V. (1962). Some ratio-type estimators in two-phase sampling. J. Amer. Statist. Assoc., 57, 628-632.
[18]	Swain, A. K. P. C. (1970). A note on the use of multiple auxiliary variables in sample surveys. Trabajos de Estadist., Inves. Oper., 21(3), 135-14.

Cite This Article

Plain Text BibTeX RIS

APA Style

Diganta Kalita. (2015). An Efficient Class of Exponential Chain Ratio Type Estimator for Finite Population Mean in Double Sampling. Science Journal of Applied Mathematics and Statistics, 3(6), 281-287. https://doi.org/10.11648/j.sjams.20150306.17

Copy | Download

ACS Style

Diganta Kalita. An Efficient Class of Exponential Chain Ratio Type Estimator for Finite Population Mean in Double Sampling. Sci. J. Appl. Math. Stat. 2015, 3(6), 281-287. doi: 10.11648/j.sjams.20150306.17

Copy | Download

AMA Style

Diganta Kalita. An Efficient Class of Exponential Chain Ratio Type Estimator for Finite Population Mean in Double Sampling. Sci J Appl Math Stat. 2015;3(6):281-287. doi: 10.11648/j.sjams.20150306.17

Copy | Download

@article{10.11648/j.sjams.20150306.17,
  author = {Diganta Kalita},
  title = {An Efficient Class of Exponential Chain Ratio Type Estimator for Finite Population Mean in Double Sampling},
  journal = {Science Journal of Applied Mathematics and Statistics},
  volume = {3},
  number = {6},
  pages = {281-287},
  doi = {10.11648/j.sjams.20150306.17},
  url = {https://doi.org/10.11648/j.sjams.20150306.17},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjams.20150306.17},
  abstract = {This paper presents a class of exponential chain ratio type estimator in double sampling for estimating finite population mean of the study variable, when the information on another additional auxiliary variable is known along with the main auxiliary variable. The property of proposed class of estimator has been studied. Comparison has been made with other competitive estimators. The proposed estimator is found to be more efficient both theoretically and empirically.},
 year = {2015}
}

Copy | Download

TY  - JOUR
T1  - An Efficient Class of Exponential Chain Ratio Type Estimator for Finite Population Mean in Double Sampling
AU  - Diganta Kalita
Y1  - 2015/12/25
PY  - 2015
N1  - https://doi.org/10.11648/j.sjams.20150306.17
DO  - 10.11648/j.sjams.20150306.17
T2  - Science Journal of Applied Mathematics and Statistics
JF  - Science Journal of Applied Mathematics and Statistics
JO  - Science Journal of Applied Mathematics and Statistics
SP  - 281
EP  - 287
PB  - Science Publishing Group
SN  - 2376-9513
UR  - https://doi.org/10.11648/j.sjams.20150306.17
AB  - This paper presents a class of exponential chain ratio type estimator in double sampling for estimating finite population mean of the study variable, when the information on another additional auxiliary variable is known along with the main auxiliary variable. The property of proposed class of estimator has been studied. Comparison has been made with other competitive estimators. The proposed estimator is found to be more efficient both theoretically and empirically.
VL  - 3
IS  - 6
ER  -

Copy | Download

Author Information

Diganta Kalita

Department of Statistics, North Lakhimpur College (Autonomous), North Lakhimpur, Assam, India

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Diganta Kalita. (2015). An Efficient Class of Exponential Chain Ratio Type Estimator for Finite Population Mean in Double Sampling. Science Journal of Applied Mathematics and Statistics, 3(6), 281-287. https://doi.org/10.11648/j.sjams.20150306.17

Copy | Download

ACS Style

Diganta Kalita. An Efficient Class of Exponential Chain Ratio Type Estimator for Finite Population Mean in Double Sampling. Sci. J. Appl. Math. Stat. 2015, 3(6), 281-287. doi: 10.11648/j.sjams.20150306.17

Copy | Download

AMA Style

Diganta Kalita. An Efficient Class of Exponential Chain Ratio Type Estimator for Finite Population Mean in Double Sampling. Sci J Appl Math Stat. 2015;3(6):281-287. doi: 10.11648/j.sjams.20150306.17

Copy | Download

@article{10.11648/j.sjams.20150306.17,
  author = {Diganta Kalita},
  title = {An Efficient Class of Exponential Chain Ratio Type Estimator for Finite Population Mean in Double Sampling},
  journal = {Science Journal of Applied Mathematics and Statistics},
  volume = {3},
  number = {6},
  pages = {281-287},
  doi = {10.11648/j.sjams.20150306.17},
  url = {https://doi.org/10.11648/j.sjams.20150306.17},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjams.20150306.17},
  abstract = {This paper presents a class of exponential chain ratio type estimator in double sampling for estimating finite population mean of the study variable, when the information on another additional auxiliary variable is known along with the main auxiliary variable. The property of proposed class of estimator has been studied. Comparison has been made with other competitive estimators. The proposed estimator is found to be more efficient both theoretically and empirically.},
 year = {2015}
}

Copy | Download

TY  - JOUR
T1  - An Efficient Class of Exponential Chain Ratio Type Estimator for Finite Population Mean in Double Sampling
AU  - Diganta Kalita
Y1  - 2015/12/25
PY  - 2015
N1  - https://doi.org/10.11648/j.sjams.20150306.17
DO  - 10.11648/j.sjams.20150306.17
T2  - Science Journal of Applied Mathematics and Statistics
JF  - Science Journal of Applied Mathematics and Statistics
JO  - Science Journal of Applied Mathematics and Statistics
SP  - 281
EP  - 287
PB  - Science Publishing Group
SN  - 2376-9513
UR  - https://doi.org/10.11648/j.sjams.20150306.17
AB  - This paper presents a class of exponential chain ratio type estimator in double sampling for estimating finite population mean of the study variable, when the information on another additional auxiliary variable is known along with the main auxiliary variable. The property of proposed class of estimator has been studied. Comparison has been made with other competitive estimators. The proposed estimator is found to be more efficient both theoretically and empirically.
VL  - 3
IS  - 6
ER  -

Copy | Download