library(fitdistrplus)
data(groundbeef)
serving <- groundbeef$serving
fitg <- fitdist(serving, "gamma")
res<-bootdist(fitg)#further accuracy estimate
#which parameter should be selected?
> summary(res)
Parametric bootstrap medians and 95% percentile CI
Median 2.5% 97.5%
shape 4.04523398 3.41773958 4.80480936
rate 0.05495878 0.04632007 0.06587446
> res$fitpart$estimate
shape rate
4.00825257 0.05441911
bootdist() always used to get more accurate parameter after fitdis().
As above example,summary(res) provide several parameters,res$fitpart$estimate provide one parameter,which one should be selected?
When you do bootstrap, you sample your data with replacement, and re-estimate the parameters. In this case you fit the distribution to a dataset that is sampled from your original dataset.
With these N estimates, you get the median, and the confidence interval.
If you want the parameter that best fits your data, you need to get it from fitdist(serving, "gamma")