Compromise Pitman estimators

In this paper, we investigate the construction of compromise estimators of location and scale, by averaging over several models selected among a specified large set of possible models. The weight given to each distribution is based on the profile likelihood, which leads to a notion of distance between distributions as we study the asymptotic behaviour of such estimators. The selection of the models is made in a minimax way, in order to choose distributions that are close to any possible distribution. We also present simulation results of such compromise estimators based on contaminated Gaussian and Student's t distributions. (C) 2011 Elsevier B.V. All rights reserved.


Published in:
Journal Of Statistical Planning And Inference, 141, 2656-2669
Year:
2011
Publisher:
Elsevier
ISSN:
0378-3758
Keywords:
Laboratories:




 Record created 2011-12-16, last modified 2018-09-13


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