Novel Log Type Class Of Estimators Under Ranked Set Sampling

This paper suggests some novel class of log type estimators for the estimation of population mean of study variable under ranked set sampling by utilizing information on population mean of auxiliary variable. The mean square error of the proposed class of estimators is obtained to the first order of...

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Bibliographic Details
Published inSankhyā. Series B (2008) Vol. 84; no. 1; pp. 421 - 447
Main Authors Bhushan, Shashi, Kumar, Anoop
Format Journal Article
LanguageEnglish
Published New Delhi Springer India 01.05.2022
Subjects
Mathematics and Statistics
Statistics
efficiency
Skewness
62D99
mean square error
Kurtosis
Ranked set sampling
62D05
Online AccessGet full text
ISSN0976-8386
0976-8394
DOI10.1007/s13571-021-00265-y

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Summary:This paper suggests some novel class of log type estimators for the estimation of population mean of study variable under ranked set sampling by utilizing information on population mean of auxiliary variable. The mean square error of the proposed class of estimators is obtained to the first order of approximation. We have compared the proposed class of estimators with some existing competitors under some specific conditions. The theoretical results are validated by a computational study using real and simulated data sets. On the lines of McIntyre ( Aust. J. Agr. Res. 3 , 385–390 1952 ), Dell ( 1969 ) and Dell and Clutter ( Biometrics 28 , 545–555 1972 ), the effect of skewness and kurtosis over the efficiency of the proposed class of estimators have also studied and reported.
ISSN:0976-8386
0976-8394
DOI:10.1007/s13571-021-00265-y