کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1148625 | 1489755 | 2016 | 18 صفحه PDF | دانلود رایگان |
• We estimate extreme value index and extreme quantiles of a heavy-tailed distribution with covariates and censoring.
• We prove asymptotic normality of our estimator of the conditional extreme value index.
• We assess the finite-sample behavior of the proposed estimators via simulations.
Estimation of the extreme-value index of a heavy-tailed distribution is addressed when some random covariate information is available and the data are randomly right-censored. A weighted kernel version of Hill’s estimator of the extreme-value index is proposed and its asymptotic normality is established. Based on this, a Weissman-type estimator of conditional extreme quantiles is constructed. A simulation study is conducted to assess the finite-sample behavior of the proposed estimators.
Journal: Journal of Statistical Planning and Inference - Volume 168, January 2016, Pages 20–37