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2021 | 22 | nr 1 | 207--216
Tytuł artykułu

A New Family of Robust Regression Estimators Utilizing Robust Regression Tools and Supplementary Attributes

Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Zaman and Bulut (2018a) developed a class of estimators for a population mean utilising LMS robust regression and supplementary attributes. In this paper, a family of estimators is proposed, based on the adaptation of the estimators presented by Zaman (2019), followed by the introduction of a new family of regression-type estimators utilising robust regression tools (LAD, H-M, LMS, H-MM, Hampel-M, Tukey-M, LTS) and supplementary attributes. The mean square error expressions of the adapted and proposed families are determined through a general formula. The study demonstrates that the adapted class of the Zaman (2019) estimators is in every case more proficient than that of Zaman and Bulut (2018a). In addition, the proposed robust regression estimators based on robust regression tools and supplementary attributes are more efficient than those of Zaman and Bulut (2018a) and Zaman (2019).The theoretical findings are supported by real-life examples. (original abstract)
Rocznik
Tom
22
Numer
Strony
207--216
Opis fizyczny
Twórcy
autor
  • University of Lahore, Islamabad, Pakistan
  • PMAS-Arid Agriculture University, Rawalpindi, Pakistan
  • Hacettepe University, Department of Statistics, Beytepe, Ankara, Turkey
  • International Islamic University, Islamabd, Pakistan
  • College of Science, Mustansiriyah University, Baghdad, Iraq
Bibliografia
  • ABD-ELFATTA,H A. M., EL-SHERPIENY, E. A., MOHAMED, S. M., ABDOU, O. F., (2010). Improvement in estimating the population mean in simple random sampling using information on auxiliary attribute, Appl. Math. Comput., Vol. 215, pp. 4198-4202.
  • KOYUNCU, N., (2012). Efficient estimators of population mean using auxiliary attributes. Applied Mathematics and Computation, Vol. 218, pp. 10900-10905.
  • NAIK, V. D., GUPTA, P. C., (1996). A note on estimation of mean with known population of an auxiliary character, J. Indian Soc. Agr. Stat., Vol. 48, pp. 151-158.
  • NASIR, A., AHMAD, I., HANIF, M., SHAHZAD, U., (2018). Robust-regression-type estimators for improving mean estimation of sensitive variables by using auxiliary information, Commun. Stat. Theory Methods, doi:10.1080/03610926.2019.1645857.
  • SHAHZAD, U., (2016). On the Estimation Of Population Mean Under Systematic Sampling Using Auxiliary Attributes, Oriental Journal Physical Sciences, Vol. 1 (1&2), pp. 17-22.
  • SHAHZAD, U., HANIF, M., KOYUNCU, N., SANAULLAH, A., (2018). On the estimation of population variance using auxiliary attribute in absence and presence of non-response, Electronic Journal of Applied Statistical Analysis, Vol. 11, pp. 608-621.
  • SUKHATME, P. V., SUKHATME, B. V., (1970). Sampling Theory of Surveys with Applications, Iowa State University Press, Ames, USA,.
  • ZAMAN, T., BULUT, H., (2018a). Modified ratio estimators for population mean using robust regression based on auxiliary attribute, IJMR, Vol. 4, pp. 1-6.
  • ZAMAN, T., BULUT, H., (2018b). Modified ratio estimators using robust regression methods, Commun. Stat. Theory Methods, doi:10.1080/03610926.2018.1441419.
  • ZAMAN, T., (2019). Improvement of modified ratio estimators using robust regression methods. Applied Mathematics and Computation, Vol. 348, pp. 627-631.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171634572

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