Generalized jackknife semi-parametric estimators of the tail index.
Gomes, M.Ivette, Martins, M.João, Neves, Manuela (2002)
Portugaliae Mathematica. Nova Série
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Displaying similar documents to “On the asymptotic exactness of Bank-Weiser's estimator.”
Generalized jackknife semi-parametric estimators of the tail index.
An asymptotically unbiased moment estimator of a negative extreme value index
Frederico Caeiro, M. Ivette Gomes (2010)
Discussiones Mathematicae Probability and Statistics
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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...
Consistency of the BIC order estimator.
Csiszár, Imre, Shields, Paul C. (1999)
Electronic Research Announcements of the American Mathematical Society [electronic only]
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Estimation of the rarefying function
P. Peruničić, Z. Glišić (1987)
Matematički Vesnik
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Shrinkage Estimation of the Proportion in Randomized Response.
S.E. Ahmed, V.K. Rohatgi (1996)
Metrika
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Asymptotic Bounds on the Errors of One-Step Methods.
L.F. Shampine (1984)
Numerische Mathematik
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The LASSO estimator: Distributional properties
Rakshith Jagannath, Neelesh S. Upadhye (2018)
Kybernetika
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The least absolute shrinkage and selection operator (LASSO) is a popular technique for simultaneous estimation and model selection. There have been a lot of studies on the large sample asymptotic distributional properties of the LASSO estimator, but it is also well-known that the asymptotic results can give a wrong picture of the LASSO estimator's actual finite-sample behaviour. The finite sample distribution of the LASSO estimator has been previously studied for the special case of...
Estimation for heavy tailed moving average process
Hakim Ouadjed, Tawfiq Fawzi Mami (2018)
Kybernetika
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In this paper, we propose two estimators for a heavy tailed MA(1) process. The first is a semi parametric estimator designed for MA(1) driven by positive-value stable variables innovations. We study its asymptotic normality and finite sample performance. We compare the behavior of this estimator in which we use the Hill estimator for the extreme index and the estimator in which we use the t-Hill in order to examine its robustness. The second estimator is for MA(1) driven by stable variables...
Optimality of the least weighted squares estimator
Libor Mašíček (2004)
Kybernetika
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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.
Asymptotic unbiased density estimators
Nicolas W. Hengartner, Éric Matzner-Løber (2009)
ESAIM: Probability and Statistics
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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. ...