Welcome to the Project "Risk Assessment with R" !
This R-Forge project was first developed to help the administrators Marie-Laure Delignette Muller,
Jean-Baptiste Denis
and Regis Pouillot to share
elements from the
three R packages they are building, "fitdistrplus",
"mc2d"
and "rebastaba".
These packages are developed in the aim to help risk assessors to
build and
study their models using Monte-Carlo simulations with R.
fitdistrplus:
Specification
of a Parametric Distribution from Data
“fitdistrplus”
is
a set of functions specifically written:
- to help to choose the best parametric distribution that fits a
given dataset;
- for a given distribution, to estimate the parameters using the
maximum likelihood method or the method of matching moments and provide
graphs and statistics to assess the fit. Specific functions were
written for censored data (right- left- and interval-censored);
- for a fitted distribution, to simulate the uncertainty in the
estimated parameters by parametric or nonparametric bootstrap
resampling.
Get the vignette
(.pdf)
Get the reference manual (.pdf)
A new stable version (Version: 0.1-2 | 2009-12-29 | Rev.: 81) is
available
on CRAN here!
mc2d:
Tools
for Two-Dimensional Monte-Carlo Simulations
"mc2d"
is a
set of functions specially written to:
- provide additional distributions: Bernoulli, triangular, PERT,
discrete empirical, generalized beta, (vectorized) multi-normal,
(vectorized) Dirichlet, (vectorized) multinomial;
- provide tools to build correlation structure between parameters:
using the Iman & Conover (1982) method, possibly on more than two
parameters;
- provide tools to build models: the package transfers easily
variability and uncertainty along a mathematical model;
- provide tools to study the model: through ad-hoc summaries and
graphics, sensitivity analyses (rank correlation on the variability or
the uncertainty dimension), etc.
Get the vignette
(.pdf)
Get the reference manual (.pdf)
Get a "stable" Beta version (Version 0.1-5, April 4th 2009, Rev 45):
This package is a Beta version and come with absolutly no
warranty!!!
Coming soon:
rebastaba:
Manipulation
of Bayesian networks within R
See here
for further details.
Feel free to join this project to:
- Test the packages;
- Develop new functions within the packages;
- Develop and post new R packages in the Risk Assessment domain ...
Back
to the
project