Premium
A General Class of Ratio‐Type Estimators Under Super‐Population Model
Author(s) -
Singh G.N.
Publication year - 2000
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/1521-4036(200007)42:3<363::aid-bimj363>3.0.co;2-2
Subject(s) - estimator , mathematics , class (philosophy) , population mean , statistics , population , type (biology) , ratio estimator , extremum estimator , sample (material) , econometrics , efficient estimator , m estimator , computer science , minimum variance unbiased estimator , demography , artificial intelligence , ecology , chemistry , chromatography , sociology , biology
The problem of constructing classes of estimators for population mean has been widely discussed by various authors under design approach in sample surveys. An attempt by Upadhyaya , Singh , and Vos (1985) has been made to combine the usual mean and ratio estimator with suitable weights in order to define a general class of estimators. This paper is an attempt to study properties of the same estimator under super‐population model. Optimum weights have also been proposed. Results have been supported with some numerical examples.