Research article

Estimation of finite population mean under PPS in presence of maximum and minimum values

  • Received: 13 November 2020 Accepted: 03 March 2021 Published: 15 March 2021
  • MSC : 62D05

  • This article deals with the estimation of the finite population mean under probability proportional to size (PPS) sampling using information on the auxiliary variable along with the rank of the auxiliary variable. We propose a ratio, product and regression type estimators by incorporating the maximum and minimum values of the study variable and the auxiliary variable. The mathematical expressions of the proposed estimators are derived up to first order of approximation. Efficiency comparisons are made on the basis of real data sets.

    Citation: Sanaa Al-Marzouki, Christophe Chesneau, Sohail Akhtar, Jamal Abdul Nasir, Sohaib Ahmad, Sardar Hussain, Farrukh Jamal, Mohammed Elgarhy, M. El-Morshedy. Estimation of finite population mean under PPS in presence of maximum and minimum values[J]. AIMS Mathematics, 2021, 6(5): 5397-5409. doi: 10.3934/math.2021318

    Related Papers:

  • This article deals with the estimation of the finite population mean under probability proportional to size (PPS) sampling using information on the auxiliary variable along with the rank of the auxiliary variable. We propose a ratio, product and regression type estimators by incorporating the maximum and minimum values of the study variable and the auxiliary variable. The mathematical expressions of the proposed estimators are derived up to first order of approximation. Efficiency comparisons are made on the basis of real data sets.



    加载中


    [1] A. Y. Al-Hossain, M. Khan, Efficiency of ratio, product, and regression estimators under maximum and minimum values, using two auxiliary variables, J. Appl. Math., 2014 (2014), 1–6.
    [2] S. Agarwal, P. Kumar, Combination of ratio and PPS estimators, Journal of Indian Society of Agricultural Statistics, 32 (1980), 81–86.
    [3] S. Ahmad, J. Shabbir, Use of extreme values to estimate finite population mean under PPS sampling scheme, Journal of Reliability and Statistical Studies, 11 (2018), 99–112.
    [4] X. Ding, H. Li, J. Lu, S. Wang, Optimal strategy estimation of random evolutionary boolean games, IEEE T. Cybernetics, 2021, doi: 10.1109/TCYB.2021.3050192.
    [5] L. K. Grover, P. Kaur, An improved estimator of the finite population mean in simple random sampling, Model Assisted Statistics and Applications, 6 (2011), 47–55. doi: 10.3233/MAS-2011-0163
    [6] S. Gupta, J. Shabbir, On improvement in estimating the population mean in simple random sampling, J. Appl. Stat., 35 (2008), 559–566. doi: 10.1080/02664760701835839
    [7] S. Hussain, S. Ahmad, S. Akhtar, A. Javed, U. Yasmeen, Estimation of finite population distribution function with dual use of auxiliary information under non-response, Plos one, 15 (2020), 1–24.
    [8] S. Hussain, S. Ahmad, M. Saleem, S. Akhtar, Finite population distribution function estimation with dual use of auxiliary information under simple and stratied random sampling, Plos one, 15 (2020), 1–30.
    [9] S. Hussain, M. Zichuan, S. Hussain, A. Iftikhar, M. Asif, S. Akhtar, et al. On estimation of distribution function using dual auxiliary information under nonresponse using simple random sampling, Journal of Probability and Statistics, 2020 (2020), 1–13.
    [10] C. Kadilar, H. Cingi, Ratio estimators in simple random sampling, Appl. Math. Comput., 151 (2004), 893–902.
    [11] C. Kadilar, H. Cingi, Improvement in estimating the population mean in simple random sampling, Appl. Math. Lett., 19 (2006), 75–79. doi: 10.1016/j.aml.2005.02.039
    [12] M. Khan, J. Shabbir, Some improved ratio, product, and regression estimators of finite population mean when using minimum and maximum values, The Scientic World Journal, 2013 (2013), 1–7.
    [13] Y. Li, H. Li, G. Zhao, Optimal state estimation for finite-field networks with stochastic disturbances, Neurocomputing, 414 (2020), 238–244. doi: 10.1016/j.neucom.2020.07.065
    [14] M. N. Murthy, Sampling theory and methods, Statistical Publishing Society, 1967.
    [15] J. Rao, Alternative estimators in pps sampling for multiple characteristics, Sankhya: The Indian Journal of Statistics, Series A, 28 (1966), 47–60.
    [16] V. N. Reddy, T. J. Rao, Modified PPS method of estimation, Sankhya, 39 (1977), 185–197.
    [17] C. E. Särndal, Sample survey theory vs. general statistical theory: Estimation of the population mean, International Statistical Review/Revue Internationale de Statistique, 40 (1972), 1–12.
    [18] H. P. Singh, R. S. Solanki, An efficient class of estimators for the population mean using auxiliary information, Commun. Stat. Theor. M., 42 (2013), 145–163. doi: 10.1080/03610926.2011.575519
    [19] R. Singh, N. S. Mangat, Elements of survey sampling, Springer Science & Business Media, 1996.
    [20] T. Srivenkataramana, D. Tracy, Transforming the study variate after PPS sampling, Metron, 37 (1979), 175–181.
    [21] P. V. Sukhatme, Sampling theory of surveys with applications, The Indian Society Of Agricultural Statistics, New Delhi, 1957.
    [22] T. Tripathi, A regression-type estimator in sampling with PPS and with replacement, Aust. N. Z. J. Stat., 11 (1969), 140–148. doi: 10.1111/j.1467-842X.1969.tb00101.x
    [23] L. N. Upadhyaya, H. P. Singh, Use of transformed auxiliary variable in estimating the finite population mean, Biometrical J., 41 (1999), 627–636. doi: 10.1002/(SICI)1521-4036(199909)41:5<627::AID-BIMJ627>3.0.CO;2-W
  • Reader Comments
  • © 2021 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(3080) PDF downloads(194) Cited by(13)

Article outline

Figures and Tables

Tables(1)

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog