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NetSimR  

Actuarial Functions for Non-Life Insurance Modelling
View on CRAN: Click here


Download and install NetSimR package within the R console
Install from CRAN:
install.packages("NetSimR")

Install from Github:
library("remotes")
install_github("cran/NetSimR")

Install by package version:
library("remotes")
install_version("NetSimR", "0.1.5")



Attach the package and use:
library("NetSimR")
Maintained by
Yiannis Parizas
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-08-20
Latest Update: 2023-12-02
Description:
Assists actuaries and other insurance modellers in pricing, reserving and capital modelling for non-life insurance and reinsurance modelling. Provides functions that help model excess levels, capping and pure Incurred but not reported claims (pure IBNR). Includes capped mean, exposure curves and increased limit factor curves (ILFs) for LogNormal, Gamma, Pareto, Sliced LogNormal-Pareto and Sliced Gamma-Pareto distributions. Includes mean, probability density function (pdf), cumulative probability function (cdf) and inverse cumulative probability function for Sliced LogNormal-Pareto and Sliced Gamma-Pareto distributions. Includes calculating pure IBNR exposure with LogNormal and Gamma distribution for reporting delay. Includes three shiny tools, one to simulate insurance claims applying reinsurance structures, fit generalised linear models and fit claims frequency or severity distributions. Methods used in the package refer to Free for All by Yiannis Parizas (2023) ; Escaping the triangle by Yiannis Parizas (2019) ; Take to excess by Yiannis Parizas (2019) .
How to cite:
Yiannis Parizas (2019). NetSimR: Actuarial Functions for Non-Life Insurance Modelling. R package version 0.1.5, https://cran.r-project.org/web/packages/NetSimR. Accessed 16 Jul. 2026.
Previous versions and publish date:
0.1.0 (2019-08-20 13:30), 0.1.1 (2021-04-22 03:50), 0.1.2 (2023-01-18 00:10), 0.1.3 (2023-09-28 08:30), 0.1.4 (2023-10-25 00:10), 0.1.5 (2023-12-02 09:10), (2026-07-12 17:50)
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