⚠️There's a newer version (2.1.2) of this package.Take me there.

rriskDistributions

rriskDistributions is a collection of functions for fitting distributions to given data or known quantiles.

The two main functions fit.perc() and fit.cont() provide users a GUI that allows to choose a most appropriate distribution without any knowledge of the R syntax. Note that this package is part of the rrisk project.

E.g., we can fit random data generated from a gamma distribution with fit.cont():

res <- fit.cont(data2fit = rgamma(n = 37, shape = 4, rate = 0.08))

This will open a new window where the user can inspect diagnostic plots for a variety of possible distributions and then choose the distribution she wants to continue working with (the chosen distribution will be stored in the res variable):

Updating to the latest version of rriskDistributions

You can track (and contribute to) development of rriskDistributions at https://github.com/mattflor/rriskDistributions. To install it, run the following command (this requires the devtools package):

devtools::install_github("mattflor/rriskDistributions")

Authors

  • Natalia Belgorodski (STAT-UP Statistical Consulting)
  • Matthias Greiner (Federal Institute for Risk Assessment, Germany)
  • Kristin Tolksdorf (Federal Institute for Risk Assessment, Germany)
  • Katharina Schueller (STAT-UP Statistical Consulting)

With contributions from

  • Lutz Göhring (Lutz Göhring Consulting)
  • Matthias Flor (Federal Institute for Risk Assessment, Germany)

Copy Link

Version

Install

install.packages('rriskDistributions')

Monthly Downloads

3,874

Version

2.1.1

License

GPL (>= 3)

Last Published

April 22nd, 2016

Functions in rriskDistributions (2.1.1)

get.logis.par

Fitting parameters of a logistic distribution from two or more quantiles
get.pois.par

Fitting parameter of Poisson distribution from one or more quantiles
get.chisq.par

Fitting parameter of a chi-square distribution from one or more quantiles
get.cauchy.par

Fitting parameters of a Cauchy distribution from two or more quantiles
fit.perc

Choosing distribution by given quantiles
get.gamma.par

Fitting parameters of a gamma distribution from two or more quantiles
get.gompertz.par

Fitting parameters of a Gompertz distribution from two or more quantiles
useFitdist

Fitting amount continuous distributions to given univariate data.
get.tnorm.par

Fitting parameters of truncated normal distribution from four or more quantiles
get.beta.par

Fitting parameters of a Beta distribution from two or more quantiles
get.t.par

Fitting parameter of a Student's t distribution from one or more quantiles
get.exp.par

Fitting parameters of an exponential distribution from one or more quantiles
rriskDistributions-package

Fitting distributions to given data or known quantiles
rriskMLEdist

Maximum likelihood fitting of univariate distributions
get.nbinom.par

Fitting parameters of a negative binomial distribution from two or more quantiles
get.unif.par

Fitting parameters of a uniform distribution from two or more quantiles
rriskMMEdist

Fitting univariate distributions by matching moments
get.norm.par

Fitting parameters of normal distribution from two or more quantiles
get.hyper.par

Fitting parameters of a hypergeometric distribution from three or more quantiles
get.norm.sd

Fitting standard deviation of a normal distribution from one or more quantiles and known mean
fit.cont

GUI for fitting continuous distributions to given data
get.chisqnc.par

Fitting parameters of a non-central chi-square distribution from one or more quantiles
rriskFitdist.perc

Fitting an amount of distribution families by given quantiles
plotDiagnostics.perc

Graphical tools for choosing distribution by given quantiles
get.pert.par

Fitting parameters of a pert distribution from four or more quantiles
get.triang.par

Fitting parameters of a triangular distribution from three or more quantiles
get.lnorm.par

Fitting parameters of a lognormal distribution from two or more quantiles
get.weibull.par

Fitting parameters of a Weibull distribution from two or more quantiles
get.f.par

Fitting parameters of a F distribution from two or more quantiles
rriskFitdist.cont

Fitting univariate distributions by maximum likelihood or by matching moments