A simple class of reduced bias kernel estimators of extreme value parameters
نویسندگان
چکیده
منابع مشابه
Bias-reduced Extreme Quantile Estimators of Weibull Tail-distributions
In this paper, we consider the problem of estimating an extreme quantile of a Weibull tail-distribution. The new extreme quantile estimator has a reduced bias compared to the more classical ones proposed in the literature. It is based on an exponential regression model that was introduced in Diebolt et al. (2008). The asymptotic normality of the extreme quantile estimator is established. We als...
متن کاملSimple Kernel Estimators for
We consider deconvolution problems where the observations are equal in distribution to Here the random variables in the sums are independent, the E i are exponentially distributed, the L i are Laplace distributed and Y has an unknown distribution F which we want to estimate. The constants i or i are given. These problems include exponential, gamma and Laplace deconvolution. We derive inversion ...
متن کاملFunctional kernel estimators of conditional extreme quantiles
We address the estimation of “extreme” conditional quantiles i.e. when their order converges to one as the sample size increases. Conditions on the rate of convergence of their order to one are provided to obtain asymptotically Gaussian distributed kernel estimators. A Weissman-type estimator and kernel estimators of the conditional tailindex are derived, permitting to estimate extreme conditio...
متن کاملImproving Second Order Reduced Bias Extreme Value Index Estimation
• Classical extreme value index estimators are known to be quite sensitive to the number k of top order statistics used in the estimation. The recently developed second order reduced-bias estimators show much less sensitivity to changes in k. Here, we are interested in the improvement of the performance of reduced-bias extreme value index estimators based on an exponential second order regressi...
متن کاملBias Reduction and Elimination with Kernel Estimators
with Kernel Estimators Stephan R. Sain1 De ember 8, 2000 SUMMARY: A great deal of resear h has fo used on improving the bias properties of kernel estimators. One proposal involves removing the restri tion of non-negativity on the kernel to onstru t \higher-order" kernels that eliminate additional terms in the Taylor's series expansion of the bias. This paper onsiders an alternative that uses a ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Computational and Mathematical Methods
سال: 2019
ISSN: 2577-7408,2577-7408
DOI: 10.1002/cmm4.1025