Commit 2917e402 authored by Manuela's avatar Manuela

removal of ifultools dependency. Use of wavScalogram instead.

parent 832e04eb
......@@ -20,14 +20,13 @@ Description: Provides a simulation framework to simulate streamflow time series
The function prsim.wave() extends the approach to multiple sites and is based on the complex wavelet transform. We further use the flexible four-parameter Kappa distribution, which allows
for the extrapolation to yet unobserved low and high flows. Alternatively, the empirical or any other distribution can be used. A detailed description of
the simulation approach for single sites and an application example can be found
in <https://www.hydrol-earth-syst-sci.net/23/3175/2019/>.
A detailed description and evaluation of the wavelet-based multi-site approach can be found in
<https://www.hydrol-earth-syst-sci-discuss.net/hess-2019-658/>
in <https://www.hydrol-earth-syst-sci.net/23/3175/2019/>. A detailed description and evaluation of the wavelet-based multi-site approach can be found in
<https://www.hydrol-earth-syst-sci-discuss.net/hess-2019-658/>.
URL: https://git.math.uzh.ch/reinhard.furrer/PRSim-devel
BugReports: https://git.math.uzh.ch/reinhard.furrer/PRSim-devel
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0), homtest, goftest, splus2R
Depends: R (>= 3.5.0), homtest, goftest, wavScalogram, splus2R
Suggests: lattice, ismev, evd, GB2
Imports: stats
Imports: stats, methods
......@@ -2,7 +2,11 @@ importFrom("homtest", "Lmoments", "rand.kappa", "par.kappa", "F.kappa")
importFrom("stats", "rnorm", "runif", "fft")
importFrom("graphics", "hist")
importFrom("goftest", "ad.test")
importFrom('wmtsa', 'wavCWT')
importFrom('splus2R', 'ifelse1')
importFrom("methods", "as")
importFrom("stats", "deltat", "time")
importFrom('wavScalogram', 'cwt_wst')
importFrom('splus2R', 'ifelse1')
# importFrom("ismev","gev.fit")
# importFrom("evd","rgev","pgev")
# importFrom("GB2","mlfit.gb2","rgb2","pgb2")
......
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......@@ -34,7 +34,7 @@ plot(sim[[1]]$Qobs[1:1000],ylab=expression(bold(paste("Specific discharge [mm/d]
for(l in 2:4){
lines(sim[[l]]$Qobs[1:1000],col=col_vect_obs[l])
}
legend('topleft',legend=c('Station 1','Station 2','Station 3','Station 4'),lty=1,col=col_vect_obs[1:4])
# legend('topleft',legend=c('Station 1','Station 2','Station 3','Station 4'),lty=1,col=col_vect_obs[1:4])
### simulated (one run)
plot(sim[[1]]$r1[1:1000],ylab=expression(bold(paste("Specific discharge [mm/d]"))),xlab="Time [d]",type="l",col=col_vect_sim[1],ylim=c(0,ylim_max),main='Stochastic simulations')
for(l in 2:4){
......
......@@ -19,7 +19,7 @@ GEV_fit <- function( xdat, ...) gev.fit( xdat, show=FALSE, ...)$mle
### GEV
out <- prsim.wave(data=runoff_multi_sites, number_sim=1, marginal="GEV", GoFtest = "KS", n_par=3, out_dir=NA)
out <- prsim.wave(data=runoff_multi_sites, number_sim=1, marginal="GEV", GoFtest = "KS", n_par=3)
### load stochastically simulated time series
......
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