Other packages > Find by keyword >

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: 2018-01-09
Latest Update:
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. Accessed 15 Jul. 2026.
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), (2026-07-09 08:15)
Other packages that cited OpVaR R package
View OpVaR citation profile
Other R packages that OpVaR depends, imports, suggests or enhances
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

footBayes  
Fitting Bayesian and MLE Football Models
This is the first package allowing for the estimation, visualization and prediction of the most wel ...
Download / Learn more Package Citations See dependency  
gscaLCA  
Generalized Structure Component Analysis- Latent Class Analysis & Latent Class Regression
Execute Latent Class Analysis (LCA) and Latent Class Regression (LCR) by using Generalized Structu ...
Download / Learn more Package Citations See dependency  
binhf  
Haar-Fisz Functions for Binomial Data
Binomial Haar-Fisz transforms for Gaussianization as in Nunes and Nason (2009). ...
Download / Learn more Package Citations See dependency  
PermAlgo  
Permutational Algorithm to Simulate Survival Data
This version of the permutational algorithm generates a dataset in which event and censoring times ...
Download / Learn more Package Citations See dependency  
gamlss.add  
Extra Additive Terms for Generalized Additive Models for Location Scale and Shape
Interface for extra smooth functions including tensor products, neural networks and decision trees. ...
Download / Learn more Package Citations See dependency  
pulseTD  
Identification of Transcriptional Dynamics using Pulse Models via 4su-Seq Data and RNA-Seq Data
A tool for analyzing the transcription, processing and degradation rates of genes by 4sU-seq (the Me ...
Download / Learn more Package Citations See dependency  

27,806

R Packages

239,283

Dependencies

73,837

Author Associations

27,807

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA