Bootstrapping uncertainty intervals for return periods
Description
Calculates and plots bootstrap uncertainty intervals for distLextremePlot
.
Usage
1 2 3 
Arguments
dlf 

nbest 
Number of best fitted distribution functions in dlf for which bootstrapping is to be done. Overriden by 
selection 
Character vector with distribution function names to be used. Suggested to keep this low. DEFAULT: NULL 
truncate 
Truncation of subsamples, see 
n 
Number of subsamples to be processed (computing time increases extraordinarily). DEFAULT: 100 
prop 
Proportion of sample to be used in each run. DEFAULT: 0.8 
returnall 
Return all simulations, instead of the aggregate confidence level? DEFAULT: FALSE 
conf.lev 
Confidence level (Proportion of subsamples within 'confidence interval'). Quantiles extracted from this value are passed to 
RPs 
Return Period vector, by default calculated internally based on log. DEFAULT: NULL 
plot 
Plot results via 
add 
Add to existing plot? DEFAULT: FALSE 
log 
Plot on a logarithmic axis. DEFAULT: TRUE 
progbars 
Show progress bar for Monte Carlo simulation? DEFAULT: TRUE 
... 
Further arguments passed to 
Details
Has not been thoroughly tested yet. Bootstrapping defaults can probably be improved.
Value
A list with (for each selection) a matrix with confidence intervals for RPs, or if returnall=TRUE, all the simulation results
Author(s)
Berry Boessenkool, berryb@gmx.de, Sept 2015
See Also
distLextreme
Examples
1 2 3  data(annMax)
dlf < distLextreme(annMax, log=TRUE, selection=c("wak","gum","gev","nor"))
dleB < distLexBoot(dlf, nbest=4, conf.lev=0.5, n=10) # n low for quick example tests

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