Generalized jackknife semi-parametric estimators of the tail index.
Gomes, M.Ivette, Martins, M.João, Neves, Manuela (2002)
Portugaliae Mathematica. Nova Série
Similarity:
Gomes, M.Ivette, Martins, M.João, Neves, Manuela (2002)
Portugaliae Mathematica. Nova Série
Similarity:
Frederico Caeiro, M. Ivette Gomes (2010)
Discussiones Mathematicae Probability and Statistics
Similarity:
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...
Csiszár, Imre, Shields, Paul C. (1999)
Electronic Research Announcements of the American Mathematical Society [electronic only]
Similarity:
P. Peruničić, Z. Glišić (1987)
Matematički Vesnik
Similarity:
S.E. Ahmed, V.K. Rohatgi (1996)
Metrika
Similarity:
L.F. Shampine (1984)
Numerische Mathematik
Similarity:
Libor Mašíček (2004)
Kybernetika
Similarity:
The present paper deals with least weighted squares estimator which is a robust estimator and it generalizes classical least trimmed squares. We will prove -consistency and asymptotic normality for any sequence of roots of normal equation for location model. The influence function for general case is calculated. Finally optimality of this estimator is discussed and formula for most B-robust and most V-robust weights is derived.
Nicolas W. Hengartner, Éric Matzner-Løber (2009)
ESAIM: Probability and Statistics
Similarity:
This paper introduces a computationally tractable density estimator that has the same asymptotic variance as the classical Nadaraya-Watson density estimator but whose asymptotic bias is zero. We achieve this result using a two stage estimator that applies a multiplicative bias correction to an oversmooth pilot estimator. Simulations show that our asymptotic results are available for samples as low as , where we see an improvement of as much as 20% over the traditionnal estimator. ...
Jan Hurt (1976)
Aplikace matematiky
Similarity: