How to do Kolmogorov-Smirnov statistic for GEV distribution in R?

Question

I am now using the extremes package to fit a generalized extreme value (GEV) distribution, and I want to use the Kolmogorov-Smirnov test to estimate the goodness of fit, but get the following error:

library(extRemes)
library(eva)
data("PORTw", package = "extRemes")
fit1 <- fevd(TMX1, PORTw, units = "deg C")
ks.test(PORTw$TMX1,"pgev",fit1$results$par[[1]],fit1$results$par[[2]],shape=fit1$results$par[[3]])

`Warning message:
In ks.test(PORTw$TMX1, "pgev", fit1$results$par[[1]], fit1$results$par[[2]],  :
  ties should not be present for the Kolmogorov-Smirnov test`

So, my question is, how to perform a Kolmogorov-Smirnov test for the GEV fit with ties? Or, is there any other goodness of fit test for fitting a distribution available in R? Thanks a lot.

Answer 1

I recommend the "EnvStats" package. You will have more versatility for goodness of fit test:

library(EnvStats)
# For a data set called X
X <- rgevd(500)
# Generalized Extreme Value (EnvStats)
egevd(X, method = "mle")# Maximum likelihood
# Goodness of fit test
gofTest(X, distribution = "gev",test = "ks")#Kolmogorov-Smirnov
gofTest(X, distribution = "gev",test = "chisq")#Chi-Squared