TITLE:
Separate-Type Estimators for Estimating Population Ratio in Post-Stratified Sampling Using Variable Transformation
AUTHORS:
Aloy Chijioke Onyeka, Chinyeaka Hostensia Izunobi, Iheanyi Sylvester Iwueze
KEYWORDS:
Variable Transformation, Separate-Type Estimator, Optimum Estimators, Ratio, Product and Regression-Type Estimators, Mean Squared Error
JOURNAL NAME:
Open Journal of Statistics,
Vol.5 No.1,
January
30,
2015
ABSTRACT: The study proposes, along the line of [1], six separate-type estimators for estimating the population ratio of two variables in post-stratified sampling, using variable transformation. Properties of the proposed estimators were obtained up to first order approximations, both for achieved sample configurations (conditional argument) and over repeated samples of fixed size n (unconditional argument). Efficiency conditions, under which the proposed separate-type estimators would perform better than the associated customary separate-type estimators in terms of having smaller mean squared errors, were obtained. Furthermore, conditions under which some of the proposed separate-type estimators would perform better than other proposed separate-type estimators were also obtained. The optimum estimators among the proposed separate-type estimators were obtained and an empirical illustration confirmed the theoretical results.