副教授
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林建希

职称:副教授

职务:

学历:博士

电子邮件:jianxilin@xmu.edu.cn

联系电话:2580656

办 公 室:物机楼513

教育经历:

南开大学基础数学本科

南开大学概率统计硕士

亚搏ag捕鱼app基础数学博士

研究方向:

重尾分布及其应用, 精算数学, 应用概率

论文:

[1] 林建希, 2007. 关于次指数分布及其相关类的一个性质. 亚搏ag捕鱼app学报(自然科学版), 46(4), 461-463.

[2] Lin, Jianxi, 2008. The general principle for precise large deviations of heavy-tailed random sums. Statistics and Probability Letters, 78(6), 749-758.

[3] Lin, Jianxi, 2008. A one-sided large deviation local limit theorem. Statistics and Probability Letters,78, 2679–2684.

[4] Lin, Jianxi, 2008. Some Blackwell-type renewal theorems for weighted renewal functions. Journal of applied probability, 45, 972-993.

[5] 林建希,2010. A Note about local subexponential distributions. 数学研究, 43(4),1-6.

[6] 林建希, 2011. 关于次指数分布性质的一个反例,亚搏ag捕鱼app学报(自然科学版),50(6),963-965.

[7] Lin, Jianxi. 2012. Second order subexponential distributions with finite mean and their applications to subordinated distributions. Journal of Theoretical Probability, 25, 834-853.

[8]Lin, Jianxi, Wang, Yuebao. 2012. New examples of heavy-tailed O-subexponential distributions and related closure properties. Statistics and Probability Letters,82, 427-432.

[9]Lin, Jianxi. 2012. Second order asymptotics for ruin probabilities in a renewal risk model with heavy-tailed claims. Insurance: Mathematics and Economics, 51, 422-429.

[10]Lin, Jianxi. 2014. Second order tail behaviour for heavy-tailed sums and their maxima with applications to ruin theory. Extremes. 17, 247–262.

[11]Lin, Jianxi. 2019. Second order tail approximation for the maxima of randomly weighted sums with applications to ruin theory and numerical examples. STATISTICS AND PROBABILITY LETTERS. 153,37-47.

[12]Lin, Jianxi. 2019. Second order tail behaviour of randomly weighted heavy-tailed sums and their maxima. Communications in Statistics - Theory and Methods. doi.org/10.1080/03610926.2019.1576900

[13]Lin, Jianxi. 2019. Second order asymptotics for ruin probabilities of the delayed renewal risk model with heavy-tailed claims. Communications in Statistics - Theory and Methods. doi.org/10.1080/03610926.2019.1648828