inst/doc/Amax.R

In martindurocher/floodStat: FloodNet Regional Frequency Analysis

## ---- fig.height=4, fig.width=4------------------------------------------
library(floodnetRfa)

## Extract the annual maximums
anData <- ExtractAmax(flow ~ date, flowStJohn, tol = 365)

## ----fig.height=4, fig.width=6-------------------------------------------

## Graph of the trend in annula maximums
plot(flow~date, anData)
fit <- with(anData, smooth.spline(date,flow))
lines(predict(fit), col = 'red', lwd = 2)
abline(h = mean(anData$flow), lty = 3, col = 'blue')

## Outcome of Mann-Kendall test
MKendall(anData$flow)

## ------------------------------------------------------------------------
fitMle <- FitAmax(anData$flow, 'gev', method = 'mle')
print(fitMle)

## ------------------------------------------------------------------------
## Fit GEV distribution using L-moments
fitLmm <-FitAmax(anData$flow, 'gev', method = 'lmom', varcov = FALSE)

## ------------------------------------------------------------------------
## Flood quantiles with uncertainty
predict(fitMle, q = c(.9,.99), se = TRUE, ci = 'delta', alpha = .1)

## ------------------------------------------------------------------------
out <- predict(fitLmm, q = c(.9,.99), ci = 'boot', nsim = 100, out.matrix = TRUE)

## Estimated Flood quantiles
print(out$pred)

## Bootstraps sample of model parameters
out$para[1:3,]

## Bootstraps sample of flood quantiles
print(out$qua[1:3,])

## ---- fig.height= 4,fig.width=6------------------------------------------
## Return level plot
plot(fitMle, ci = TRUE)

## ------------------------------------------------------------------------
## Anderson-Darling goodness of fit test
GofTest(fitLmm, nsim = 500)

## ------------------------------------------------------------------------
## 
FitAmax(anData$flow, 'ln3', method = 'lmom', varcov =  FALSE)

## ------------------------------------------------------------------------
## Function that compute the AIC for a given distribution
FAIC <- function(d)
   AIC(FitAmax(anData$flow, d, method = 'mle', varcov =  FALSE))

## AIC of all distribution
sapply(c('gev','glo','ln3','pe3'), FAIC)

## Automatic selection of the distribution
FitAmax.auto(anData$flow, method = 'mle', tol.gev = 2)