Estimation of the parameters of generalized linear models in the analysis of actuarial risks

Methods of estimating the parameters of generalized linear models for the case of paying insurance premiums to clients are considered. The iterative-recursive weighted least squares method, the Adam optimization algorithm, and the Monte Carlo method for Markov chains were implemented. Insurance indi...

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Bibliographic Details
Main Authors: Roman Panibratov, Petro Bidyuk
Format: Article
Language:Ukrainian
Published: Igor Sikorsky Kyiv Polytechnic Institute 2023-06-01
Series:Sistemnì Doslìdženâ ta Informacìjnì Tehnologìï
Subjects:
Online Access:http://journal.iasa.kpi.ua/article/view/285518
Description
Summary:Methods of estimating the parameters of generalized linear models for the case of paying insurance premiums to clients are considered. The iterative-recursive weighted least squares method, the Adam optimization algorithm, and the Monte Carlo method for Markov chains were implemented. Insurance indicators and the target variable were randomly generated due to the problem of public access to insurance data. For the latter, the normal and exponential law of distribution and the Pareto distribution with the corresponding link functions were used. Based on the quality metrics of model learning, conclusions were made regarding their construction quality.
ISSN:1681-6048
2308-8893