descdist {fitdistrplus}R Documentation

Description of an empirical distribution for non-censored data

Description

Computes descriptive parameters of an empirical distribution for non-censored data and provides a skewness-kurtosis plot.

Usage

descdist(data,discrete=FALSE,boot=NULL,graph=TRUE)

Arguments

data A numeric vector.
discrete If TRUE, the distribution is considered as discrete.
boot If not NULL, boot values of skewness and kurtosis are plotted from bootstrap samples of data. boot must be fixed in this case to an integer above 10.
graph If FALSE, the graph is not plotted.

Details

Minimum, maximum, median, mean, sample sd, sample skewness and sample kurtosis values are printed. A skewness-kurtosis plot such as the one proposed by Cullen and Frey (1999) is given for the empirical distribution. On this plot, values for common distributions are also displayed as a tools to help the choice of distributions to fit to data. In order to take into account the uncertainty of the estimated values of kurtosis and skewness, the data set may be boostraped by fixing the argument boot to an integer above 10. boot values of skewness and kurtosis corresponding to the boot bootstrap samples are then computed and reported in blue color on the skewness-kurtosis plot.

If discrete is TRUE, these common distributions are the Poisson, negative binomial and normal distributions. If discrete is FALSE, these are uniform, normal, lognormal, beta and gamma distributions. The Weibull distribution is not represented on the graph but it is indicated on the legend that shapes close to lognormal and gamma distributions may be obtained with this distribution.

Value

descdist returns a list with 7 components,

min the minimum value
max the maximum value
median the median value
mean the mean value
sd the standard deviation sample value
skewness the skewness sample value
kurtosis the kurtosis sample value

Author(s)

Marie-Laure Delignette-Muller ml.delignette@vet-lyon.fr

References

Cullen AC and Frey HC (1999) Probabilistic techniques in exposure assessment. Plenum Press, USA, pp. 81-159. Evans M, Hastings N and Peacock B (2000) Statistical distributions. John Wiley and Sons Inc.

See Also

plotdist

Examples

x1<-c(6.4,13.3,4.1,1.3,14.1,10.6,9.9,9.6,15.3,22.1,13.4,
13.2,8.4,6.3,8.9,5.2,10.9,14.4)
descdist(x1)
descdist(x1,boot=1000)

x2<-c(rep(4,1),rep(2,3),rep(1,7),rep(0,12))
descdist(x2,discrete=TRUE)

x3<-rbeta(100,shape1=0.05,shape2=1)
descdist(x3,boot=1000)

[Package fitdistrplus version 0.1-1 Index]