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Concomitants and linear estimators in an i-dimensional extremal model.

M. Ivette Gomes — 1985

Trabajos de Estadística e Investigación Operativa

We consider here a multivariate sample X = (X > ... > X), 1 ≤ j ≤ n, where the X, 1 ≤ j ≤ n, are independent i-dimensional extremal vectors with suitable unknown location and scale parameters λ and δ respectively. Being interested in linear estimation of these parameters, we consider the multivariate sample Z, 1 ≤ j ≤ n, of the order statistic of largest values and their concomitants, and the best linear unbiased estimators of λ and δ based on such multivariate sample. Computational...

Comparison at optimal levels of classical tail index estimators: a challenge for reduced-bias estimation?

M. Ivette GomesLígia Henriques-Rodrigues — 2010

Discussiones Mathematicae Probability and Statistics

In this article, we begin with an asymptotic comparison at optimal levels of the so-called "maximum likelihood" (ML) extreme value index estimator, based on the excesses over a high random threshold, denoted PORT-ML, with PORT standing for peaks over random thresholds, with a similar ML estimator, denoted PORT-MP, with MP standing for modified-Pareto. The PORT-MP estimator is based on the same excesses, but with a trial of accommodation of bias on the Generalized Pareto model underlying those excesses....

An asymptotically unbiased moment estimator of a negative extreme value index

Frederico CaeiroM. Ivette Gomes — 2010

Discussiones Mathematicae Probability and Statistics

In this paper we consider a new class of consistent semi-parametric estimators of a negative extreme value index, based on the set of the k largest observations. This class of estimators depends on a control or tuning parameter, which enables us to have access to an estimator with a null second-order component of asymptotic bias, and with a rather interesting mean squared error, as a function of k. We study the consistency and asymptotic normality of the proposed estimators. Their finite sample...

The extreme value Birnbaum-Saunders model, its moments and an application in biometry

M. Ivette GomesMarta FerreiraVíctor Leiva — 2012

Biometrical Letters

The Birnbaum-Saunders (BS) model is a life distribution that has been widely studied and applied. Recently, a new version of the BS distribution based on extreme value theory has been introduced, named the extreme value Birnbaum-Saunders (EVBS) distribution. In this article we provide some further details on the EVBS models that can be useful as a supplement to the existing results. We use these models to analyse real survival time data for patients treated with alkylating agents for multiple myeloma....

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