This course covers the modeling claim propension, claim counts, claim severities and claim duration with generalized linear models (GLM), generalized additive models (GAM and GAMLSS), mixed models (GLMM) and generalized non-linear models (GNM).
The analysis is conducted using R, leveraging its statistical capabilities to model and predict insurance costs based on various factors.
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1. Introduction/: Contains materials for the introductory session on R and descriptive analysis.
- 1. Brief Introduction to R and Descriptive Analysis of the Dataset.Rmd: A script for conducting descriptive analysis of the dataset.
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2. GLM/: Contains materials for the session on Generalized Linear Models.
- GLM.Rmd: A script for fitting the GLM model to the data and analyzing results.
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3. GAM/: Contains materials for the session on Generalized Additive Models.
- GAM.Rmd: A script for fitting the GAM model to the data and analyzing results.
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data/: Contains the datasets used for analysis.
mtpl_fr.rda: dataset for the practical sessions.mtpl_be.rda: dataset for the project.
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project/: Contains instructions for the project.
To run the scripts in this project, ensure you have R and RStudio installed on your machine. Additionally, you'll need to install the required R packages.