Moving from \citet{Rao1991} regression estimator, a class of biased estimators for the unknown mean of a survey variable is proposed when auxiliary information is available. The bias and the mean square error of the estimators belonging to the class are obtained to the first order of approximation and the expression for the optimum parameters minimizing the mean square error is given in a closed form. A simple condition allowing for outperforming the classical regression estimator is worked out. In order to investigate the performance of some estimators upon the regression one, a simulation study is carried out when some population parameters are supposed to be unknown.
An improved class of estimators for the population mean
PERRI, PIER FRANCESCO
2011-01-01
Abstract
Moving from \citet{Rao1991} regression estimator, a class of biased estimators for the unknown mean of a survey variable is proposed when auxiliary information is available. The bias and the mean square error of the estimators belonging to the class are obtained to the first order of approximation and the expression for the optimum parameters minimizing the mean square error is given in a closed form. A simple condition allowing for outperforming the classical regression estimator is worked out. In order to investigate the performance of some estimators upon the regression one, a simulation study is carried out when some population parameters are supposed to be unknown.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
