LRMoE.jl: A Package for Insurance Loss Modelling Using a Mixture of Experts Regression Model

Author: Spark C. Tseung, Andrei L. Badescu, Tsz Chai Fung, X. Sheldon Lin

Publication date: 01-02-2022

Version: Current

Language available: Bilingual

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This paper introduces a new Julia package, LRMoE, statistical software tailor-made for actuarial applications which allows actuarial researchers and practitioners to model and analyze insurance loss frequencies and severities using the Logit-weighted Reduced Mixture of Experts (LRMoE) model. LRMoE offers several new distinctive features which are motivated by various actuarial applications and mostly cannot be achieved using existing packages for mixture models.

Categories: Research

Topics: Data science

Pages: 32

Format: PDF

Accession no.: rp222019