Distributions: Distributions in the PoweR package

In PoweR: Computation of Power and Level Tables for Hypothesis Tests

Description

Random variate generation for many standard probability distributions are available in the PoweR package.

Details

The functions for the random variate generation are named in the form lawxxxx.

For the Laplace distribution see law0001.Laplace.

For the Normal distribution see law0002.Normal.

For the Cauchy distribution see law0003.Cauchy.

For the Logistic distribution see law0004.Logistic.

For the Gamma distribution see law0005.Gamma.

For the Beta distribution see law0006.Beta.

For the Uniform distribution see law0007.Uniform.

For the Student distribution see law0008.Student.

For the Chi-Squared distribution see law0009.Chisquared.

For the Log Normal distribution see law0010.LogNormal.

For the Weibull distribution see law0011.Weibull.

For the Shifted Exponential distribution see law0012.ShiftedExp.

For the Power Uniform distribution see law0013.PowerUnif.

For the Average Uniform distribution see law0014.AverageUnif.

For the UUniform distribution see law0015.UUnif.

For the VUniform distribution see law0016.VUnif.

For the Johnson SU distribution see law0017.JohnsonSU.

For the Tukey distribution see law0018.Tukey.

For the Location Contaminated distribution see law0019.LocationCont.

For the Johnson SB distribution see law0020.JohnsonSB.

For the Skew Normal distribution see law0021.SkewNormal.

For the Scale Contaminated distribution see law0022.ScaleCont.

For the Generalized Pareto distribution see law0023.GeneralizedPareto.

For the Generalized Error distribution see law0024.GeneralizedError.

For the Stable distribution see law0025.Stable.

For the Gumbel distribution see law0026.Gumbel.

For the Frechet distribution see law0027.Frechet.

For the Generalized Extreme Value distribution see law0028.GeneralizedExtValue.

For the Generalized Arcsine distribution see law0029.GeneralizedArcsine.

For the Folded Normal distribution see law0030.FoldedNormal.

For the Mixture Normal distribution see law0031.MixtureNormal.

For the Truncated Normal distribution see law0032.TruncatedNormal.

For the Normal with outliers distribution see law0033.Nout.

For the Generalized Exponential Power distribution see law0034.GeneralizedExpPower.

For the Exponential distribution see law0035.Exponential.

For the Asymmetric Laplace distribution see law0036.AsymmetricLaplace.

For the Normal-inverse Gaussian distribution see law0037.NormalInvGaussian.

For the Asymmetric Power Distribution see law0038.AsymmetricPowerDistribution.

For the modified Asymmetric Power Distribution see law0039.modifiedAsymmetricPowerDistribution.

For the Log-Pareto-tail-normal distribution see law0040.Log-Pareto-tail-normal.

Author(s)

P. Lafaye de Micheaux, V. A. Tran

References

Pierre Lafaye de Micheaux, Viet Anh Tran (2016). PoweR: A Reproducible Research Tool to Ease Monte Carlo Power Simulation Studies for Goodness-of-fit Tests in R. Journal of Statistical Software, 69(3), 1–42. doi:10.18637/jss.v069.i03

See Also

The CRAN task view on distributions, https://CRAN.R-project.org/view=Distributions, mentioning several CRAN packages for additional distributions.

PoweR documentation built on May 2, 2019, 2:09 p.m.