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OpVaR  

Statistical Methods for Modelling Operational Risk
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("OpVaR", "1.2")



Attach the package and use:
library("OpVaR")
Maintained by
Christina Zou
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-05-29
Latest Update: 2021-09-08
Description:
Functions for computing the value-at-risk in compound Poisson models. The implementation comprises functions for modeling loss frequencies and loss severities with plain, mixed (Frigessi et al. (2012) ) or spliced distributions using Maximum Likelihood estimation and Bayesian approaches (Ergashev et al. (2013) ). In particular, the parametrization of tail distributions includes the fitting of Tukey-type distributions (Kuo and Headrick (2014) ). Furthermore, the package contains the modeling of bivariate dependencies between loss severities and frequencies, Monte Carlo simulation for total loss estimation as well as a closed-form approximation based on Degen (2010) to determine the value-at-risk.
How to cite:
Christina Zou (2018). OpVaR: Statistical Methods for Modelling Operational Risk. R package version 1.2, https://cran.r-project.org/web/packages/OpVaR
Previous versions and publish date:
1.0.5 (2018-05-29 06:59), 1.0 (2018-01-09 19:28), 1.1.1 (2020-07-02 09:30), 1.2 (2021-09-08 18:00)
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