bootdistcens {fitdistrplus}R Documentation

Bootstrap simulation of uncertainty for censored data

Description

Uses nonparametric bootstrap resampling in order to simulate uncertainty in the parameters of the distribution fitted to censored data.

Usage

bootdistcens(f, niter=999)
## S3 method for class 'bootdistcens':
print(x,...)
## S3 method for class 'bootdistcens':
plot(x,...)
## S3 method for class 'bootdistcens':
summary(object,...)

Arguments

f An object of class 'fitdistcens' result of the function fitdistcens.
niter The number of samples drawn by bootstrap.
x an object of class 'bootdistcens'.
object an object of class 'bootdistcens'.
... further arguments passed to other methods

Details

Samples are drawn by non parametric bootstrap (resampling with replacement from the data set). On each bootstrap sample the function mledistcens is used to estimate bootstrapped values of parameters. When mledistcens fails to converge, NA values are returned. Medians and 2.5 and 97.5 percentiles are computed by removing NA values. The number of iterations for which mledistcens converges is printed in the summary with the medians and the 95 percent confidence intervals of parameters (2.5 and 97.5 percentiles).

The plot of an object of class 'bootdistcens' consists in a scatterplot or a matrix of scatterplots of the bootstrapped values of parameters. It uses the function stripchart when the fitted distribution is characterized by only one parameter, and the function plot in other cases. In these last cases, it provides a representation of the joint uncertainty distribution of the fitted parameters.

Value

bootdistcens returns an object of class 'bootdistcens', a list with 3 components,

estim a data frame containing the boostrapped values of parameters.
converg a vector containing the codes for convergence obtained when using mledist on each bootraped data set or NULL if momdist is used.
CI bootstrap medians and 95 percent confidence intervals of parameters.

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. 181-241.

See Also

fitdistcens and mledistcens.

Examples

d1<-data.frame(
left=c(1.73,1.51,0.77,1.96,1.96,-1.4,-1.4,NA,-0.11,0.55,
    0.41,2.56,NA,-0.53,0.63,-1.4,-1.4,-1.4,NA,0.13),
right=c(1.73,1.51,0.77,1.96,1.96,0,-0.7,-1.4,-0.11,0.55,
    0.41,2.56,-1.4,-0.53,0.63,0,-0.7,NA,-1.4,0.13))
f1<-fitdistcens(d1, "norm")
b1<-bootdistcens(f1)
b1
summary(b1)
plot(b1)


[Package fitdistrplus version 0.1-1 Index]