Asymptotically Normal Estimators of the Gerber-Shiu Function in Classical Insurance Risk Model

被引：6

作者：

Su, Wen ^{[1
]}

Yu, Wenguang ^{[1
]}

机构：

[1] Shandong Univ Finance & Econ, Sch Insurance, Jinan 250014, Peoples R China

来源：

MATHEMATICS | 2020年 / 8卷 / 10期

基金：

中国国家自然科学基金;

关键词：

Gerber-Shiu function; Laguerre series; classical risk model; asymptotic normality; NONPARAMETRIC-ESTIMATION; DISCOUNTED PENALTY; RUIN PROBABILITY;

D O I：

10.3390/math8101638

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

Nonparametric estimation of the Gerber-Shiu function is a popular topic in insurance risk theory. Zhang and Su (2018) proposed a novel method for estimating the Gerber-Shiu function in classical insurance risk model by Laguerre series expansion based on the claim number and claim sizes of sample. However, whether the estimators are asymptotically normal or not is unknown. In this paper, we give the details to verify the asymptotic normality of these estimators and present some simulation examples to support our result.

引用

页数：11

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