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fitdistrplus (version 0.1-2)

descdist: 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.

Value

  • descdist returns a list with 7 components,
  • minthe minimum value
  • maxthe maximum value
  • medianthe median value
  • meanthe mean value
  • sdthe standard deviation sample value
  • skewnessthe skewness sample value
  • kurtosisthe kurtosis sample value

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, the represented 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.

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

Run this code
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)

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