Calculate 90% confidence interval on extreme value distributions in R using lmomco

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I am using a 4-parameter kappa distribution to estimate the annual exceedance frequency of extreme precipitation observations using an annual maxima series AMS. The data is fitted using L-Moments via R's lmomco library.

I would like to calculate the 90% confidence bounds of the estimates but see no clear way to do this via lmomco. Any suggestions?

(Edited to add a subset of the AMS series data)

library(lmomco)

AMS <- c(45.045, 68.926, 60.06, 46.904, 60.06, 57.343, 44.187, 35.321, 47.905, 39.325, 
         39.897, 46.904, 46.904, 34.1288, 32.1687, 43.9293, 40.4703, 48.8872, 35.1665, 
         34.0135, 37.5878, 35.3971, 67.3352, 35.3971, 50.6167)

moments=lmoms(AMS, nmom=4)

parameters=parkap(moments, checklmom=FALSE) 

RPs=c(10, 20, 50, 100, 200, 500, 1000, 2000, 5000, 10000)
NEPs=1-(1/RPs)

out=quakap(NEPs, para=parameters)

write.table(out, file='R_Kappa_COQ.csv', sep=',')
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