GEMAct：一个用于非寿险（再保险）建模的 Python 包
GEMAct: a Python package for non-life (re)insurance modeling
AI总结：
本文介绍了基于集体风险模型的精算 Python 包 gemact，新增多种概率分布并实现 AEP 算法以计算相关随机变量和的分布，支持风险定价、转移、聚合与准备金等非寿险应用。
摘要：
本文介绍了基于集体风险模型的精算建模 Python 包 gemact。该库支持风险定价与风险转移、损失聚合及损失准备金等应用。我们在 scipy 的基础上新增了概率分布，包括 (a, b, 0) 和 (a, b, 1) 离散分布，Archimedean 族、Gaussian、Student t 及 Fundamental copula。我们实现了 AEP 算法，用于在给定由 copula 指定的依赖结构下，计算非负相关随机变量和的累积分布函数。每节开头均介绍了理论框架，以便读者充分理解背后的精算模型。
英文摘要：
This paper introduces $\textbf{gemact}$, a $\textbf{Python}$ package for actuarial modelling based on the collective risk model. The library supports applications to risk costing and risk transfer, loss aggregation, and loss reserving. We add new probability distributions to those available in $\textbf{scipy}$, including the (a, b, 0) and (a, b, 1) discrete distributions, copulas of the Archimedean family, the Gaussian, the Student t and the Fundamental copulas. We provide an implementation of the AEP algorithm for calculating the cumulative distribution function of the sum of dependent, non-negative random variables, given their dependency structure specified with a copula. The theoretical framework is introduced at the beginning of each section to give the reader with a sufficient understanding of the underlying actuarial models.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
