Abstract
A sample is taken from a population consisting of K subpopulations. The observations consist of two components (P,Y) where Y is of real interests and P is a conditional probability to help identify as to which subpopulation the observations come from. A general estimation procedure for estimating the subpopulation means of Y is introduced. It is the regression coefficient estimation when Y is regressed on the conditional probability. When the conditional probability is accurately given, the estimator is unbiased. The notion of a fuzzy partition is introduced. It is suggested that the estimation procedure using a fuzzy partition will reduce the bias. A simulation study is conducted to cornpare the proposed estimator (estimator after fuzzy c:lassification) with the usual estimator (estimator after hardclassification) and Selen's (1986) estimator.
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