Estimation of tail probability is of interest in various applications. Given a parametric model, a natural approach is maximum likelihood estimationAlthough the resulting estimator is asymptotically efficient, the large sam-ple property is often not trustworthy for estimating small tail probabilities.We introduce a new estimator for the parameters, the Maximum Lq-Like-lihood Estimator (MLqE), based on Havrda and Charv·t entropy function.
Estimation of Tail Probability via the Maximum Lq-Likelihood Method / Ferrari, Davide. - STAMPA. - 1:(2007), pp. 263-263. (Intervento presentato al convegno Joint Statistical Meetings tenutosi a Salt Lake City, USA nel July 29 - August2, 2007).
Estimation of Tail Probability via the Maximum Lq-Likelihood Method
FERRARI, Davide
2007
Abstract
Estimation of tail probability is of interest in various applications. Given a parametric model, a natural approach is maximum likelihood estimationAlthough the resulting estimator is asymptotically efficient, the large sam-ple property is often not trustworthy for estimating small tail probabilities.We introduce a new estimator for the parameters, the Maximum Lq-Like-lihood Estimator (MLqE), based on Havrda and Charv·t entropy function.
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