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Estimation of the maximal moment exponent with censored data
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Autores
Orientador(es)
Resumo(s)
Heavy-tailed distributions have been used to model phenomena in which extreme events occur with high probability. In these type of occurrences, it is likely that extreme events are not observable after a certain threshold. Appropriate estimators are needed to deal with this type of censored data. We show that the well-known Hill-Hall estimator is unable to deal with censored data and yields highly biased estimates. We propose and study an unbiased modified maximum likelihood estimator, as well as a truncated tail regression estimator. We assess the expected value and the variance of these estimators in the cases of stable- and Pareto-distributed data.
Descrição
Palavras-chave
Extreme Events Heavy Tail Hill Estimator Pareto Distribution Stable Distribution
Contexto Educativo
Citação
Crato, Nuno .(2000). “Estimation of the maximal moment exponent with censored data”. Communications in Statistics - Simulation and Computation, Vol. 29, No. 4: pp. 1239-1253. (Search PDF in 2023)
Editora
Taylor & Francis