In MartinRoth/gevflex: Flexible GEV estimation

library(data.table)
library(ggplot2)
library(evdflex)
library(evd)

The following example data will help to demonstrate the usage of this package.

data <- fread("../tests/testthat/testData.txt")
data <- data[, 1 : 4, with = FALSE]
setnames(data, c("Station", "m10", "m20", "Date"))
setcolorder(data, c("Date", "Station", "m10", "m20"))
invisible(data[, Date := as.Date(paste0(Date), "%Y%m%d")])
setkey(data, Date, Station)

knitr::kable(head(data))
knitr::kable(tail(data))

Simple parameter model

fpar <- function(p, xpar) {
    loc   <- p[1]
    scale <- p[2]
    shape <- p[3]
    list(loc = loc, scale = scale, shape = shape)
  }

Fit for fixed 10 min data and for arbitrary 10 min data using the range likelihood.

fitSimple <- FitGevFlex(data[, m10], start = c(7, 2.5, 0.05), fpar = fpar)
fitGrouped  <- FitGevFlex(data[, .(m10, m20)], start = c(7, 2.5, 0.05),
                        fpar = fpar, likelihood = "grouped")

setkey(data, m10)
invisible(data[, x := qgev((1:.N)/(.N+1))])
invisible(data[, fitSimple := qgev((1:.N)/(.N+1),
                                   loc   = fitSimple$estimate[1],
                                   scale = fitSimple$estimate[2],
                                   shape = fitSimple$estimate[3]
                                   )])
invisible(data[, fitGrouped := qgev((1:.N)/(.N+1),
                                   loc   = fitGrouped$estimate[1],
                                   scale = fitGrouped$estimate[2],
                                   shape = fitGrouped$estimate[3]
                                   )])
ggplot(data, aes(y = m10, x = x)) + geom_point() +
  geom_point(aes(y = m20), shape = 2) + 
  geom_line(aes(y = fitSimple), lty = 2, col = 2) +
  geom_line(aes(y = fitGrouped), lty = 2, col = 4)