Murthy’s Estimator in Unequal Probability Inverse Adaptive Cluster Sampling

Prayad Sangngam

Abstract


This paper derives a Murthy’s unbiased estimator of population total under unequal probability inverse sampling. A general unequal probability inverse sampling is combined with adaptive cluster sampling. An unbiased estimator of population total and its variance estimator are given using Murthy’s approach. The general unequal probability inverse adaptive cluster sampling and general equal probability inverse adaptive cluster sampling are compared using simulation study based on real life data. The results indicate that the general unequal probability inverse adaptive cluster sampling has a small coefficient of variation for estimates compared to equal probability inverse adaptive cluster sampling. When the coefficients of correlation between study variable and probability of selection units increase, the coefficient of variation decreases.


Full Text: PDF DOI: 10.5539/mas.v6n11p20

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Modern Applied Science   ISSN 1913-1844 (Print)   ISSN 1913-1852 (Online)

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