Usage

Usage#

Installation#

GEMAct can be easily installed via pip:

pip install gemact

In case you are installing GEMAct within Google Colab, please make sure to restart the kernel or to refresh the page before using it.

Tutorials#

Users might be interested in the following Jupyter notebooks available on GitHub. We provide several examples to familiarize with GEMAct functionalities.

  • Click here to check the replication material of the GEMAct manuscript.

  • Click here to check the supplementary code to replicate Section 3.6 Comparison of the methods for computing the aggregate loss distribution and Section 3.7. Comparison with aggregate FFT implementation of the GEMAct manuscript.

  • Click here to check the supplementary code to replicate Section 4.2. Comparison of the methods for computing the cdf of the GEMAct manuscript.

  • Click here to check the supplementary material on Section 5.ipynb provides the supplementary code to replicate Section 5.2.1. Comparasion with chain ladder of the GEMAct manuscript.

  • Click here to check the supplementary material on the data generator.Rmd provides the R code to simulate the data generation process used in Section 5. Loss Reserve and Appendix C Claims Reserving with the Fisher-Lange of the GEMAct manuscript. It also includes the algorithm to compute the PE of the reserve in Section 5.2.1. Comparasion with chain ladder.

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