Sample Survey Calibration: An Informationtheoretic perspective
Martin Wittenberg ()
No 41, SALDRU Working Papers from Southern Africa Labour and Development Research Unit, University of Cape Town
We show that the pseudo empirical maximum likelihood estimator can be recast as a calibration estimator. The process of estimating the probabilities pk of the distribution function can be done also in a maximum entropy framework. We suggest that a minimum cross-entropy estimator has attractive theoretical properties. A Monte Carlo simulation suggests that this estimator outperforms the PEMLE and the Horvitz-Thompson estimator. This is a joint SALDRU/DataFirst Working Paper as part of the Mellon Data Quality Project. For more information about the project visit www.datafirst.uct.ac.za.
Keywords: sample weights; calibration; pseudo-empirical maximum likelihood estimation; cross entropy (search for similar items in EconPapers)
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