
Summary: This paper considers the problem of estimating the population proportion of a categorical variable using the calibration framework. Different situations are explored according to the level of auxiliary information available and the theoretical properties are investigated. A new class of estimator based upon the proposed calibration estimators is also defined, and the optimal estimator in the class, in the sense of minimal variance, is derived. Finally, an estimator of the population proportion, under new calibration conditions, is defined. Simulation studies are considered to evaluate the performance of the proposed calibration estimators via the empirical relative bias and the empirical relative efficiency, and favourable results are achieved.
Finite Population, Statistics, Auxiliary Information, calibración, información auxiliar, auxiliary information, finite population, estimators, calibration, HA1-4737, Estimators, Calibration, Sampling theory, sample surveys, sampling design, estimadores, población finita, Sampling Design, diseño muestral
Finite Population, Statistics, Auxiliary Information, calibración, información auxiliar, auxiliary information, finite population, estimators, calibration, HA1-4737, Estimators, Calibration, Sampling theory, sample surveys, sampling design, estimadores, población finita, Sampling Design, diseño muestral
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