diff --git a/PRSim/DESCRIPTION b/PRSim/DESCRIPTION
index 76a9bf5563474518bb4f1be9115015cf3fbee1b5..49ba54b33347c105d746173024de6fe5833d76b6 100644
--- a/PRSim/DESCRIPTION
+++ b/PRSim/DESCRIPTION
@@ -2,7 +2,7 @@ Package: PRSim
Type: Package
Title: Stochastic Simulation of Streamflow Time Series using Phase Randomization
Version: 1.4-3
-Date: 2023-06-12
+Date: 2023-06-13
Authors@R: c(person("Manuela", "Brunner", role = c("aut", "cre"),
email = "manuela.brunner@env.ethz.ch",
comment = c(ORCID = "0000-0001-8824-877X")),
@@ -38,4 +38,4 @@ LazyData: true
Depends: R (>= 3.5.0)
Suggests: lattice, ismev, evd, GB2, boot, MASS
Imports: stats, methods, lmomco, mev, goftest, wavScalogram, splus2R
-RoxygenNote: 7.1.2
+RoxygenNote: 7.2.3
diff --git a/PRSim/man/PRSim-package.Rd b/PRSim/man/PRSim-package.Rd
index 17b92427aea102b470b0c7ecdce9b491600bf222..e3e179e7095ae91046d4a106d554c9b667d6a463 100644
--- a/PRSim/man/PRSim-package.Rd
+++ b/PRSim/man/PRSim-package.Rd
@@ -36,7 +36,7 @@ Brunner, M. I., and E. Gilleland (2021). Spatial compound hot-dry events in the
}
\keyword{ package }
\examples{
-\dontrun{
+\run_dontrun{
demo("PRSim")
demo("PRSim-validate")
demo("PRSim_wave")
diff --git a/PRSim/man/fun_stoch_sim.Rd b/PRSim/man/fun_stoch_sim.Rd
index 86c17bae99cdef8482dac1868a7ab24e6b0d21a2..8c177b94d52638d425e203273c45e6be7467d050 100644
--- a/PRSim/man/fun_stoch_sim.Rd
+++ b/PRSim/man/fun_stoch_sim.Rd
@@ -67,17 +67,19 @@ rGEV <- function(n, theta) rgev(n, theta[1], theta[2], theta[3])
pGEV <- function(x, theta) pgev(x, theta[1], theta[2], theta[3])
GEV_fit <- function( xdat, ...) gev.fit( xdat, ...)$mle
-\dontrun{ # The following call requires 5 seconds to execute
+\run_dontrun{ # The following call requires 5 seconds to execute
out <- prsim( runoff[ runoff$YYYY<1978, ], "Qobs", 1,
marginal="GEV", n_par=3, verbose=FALSE, marginalpar=FALSE,
show=FALSE) # Supress 'gev.fit' output.
}
## (2) example with generalized Beta distribution of the second kind
+\run_dontrun{
require( "GB2")
rGB2 <- function(n, theta) rgb2(n, theta[1], theta[2], theta[3], theta[4])
pGB2 <- function(x, theta) pgb2(x, theta[1], theta[2], theta[3], theta[4])
GB2_fit <- function( xdat, ...) ml.gb2( xdat, ...)$opt1$par
+}
\dontrun{ # The following call requires half minute or so to execute. Some warnings are issued
out <- prsim( runoff[ runoff$YYYY<1987, ], "Qobs", 1, suppWarn=TRUE,
diff --git a/PRSim/man/fun_stoch_sim_wave.Rd b/PRSim/man/fun_stoch_sim_wave.Rd
index f690c89025a224699e9ce27681577478c2e12f82..97ab4eaf65a7279d17836d6801e3ecbd8f124e52 100644
--- a/PRSim/man/fun_stoch_sim_wave.Rd
+++ b/PRSim/man/fun_stoch_sim_wave.Rd
@@ -69,7 +69,7 @@ rGEV <- function(n, theta) rgev(n, theta[1], theta[2], theta[3])
pGEV <- function(x, theta) pgev(x, theta[1], theta[2], theta[3])
GEV_fit <- function( xdat, ...) gev.fit( xdat, ...)$mle
-\dontrun{ # The following call requires 5 seconds to execute
+\run_dontrun{ # The following call requires 5 seconds to execute
prsim.wave(runoff_multi_sites, "Qobs", 1,
marginal="GEV", n_par=3, verbose=FALSE, marginalpar=FALSE,
show=FALSE)
@@ -77,12 +77,14 @@ prsim.wave(runoff_multi_sites, "Qobs", 1,
}
## (2) example with generalized Beta distribution of the second kind
+\run_dontrun{
require( "GB2")
rGB2 <- function(n, theta) rgb2(n, theta[1], theta[2], theta[3], theta[4])
pGB2 <- function(x, theta) pgb2(x, theta[1], theta[2], theta[3], theta[4])
GB2_fit <- function( xdat, ...) ml.gb2( xdat, ...)$opt1$par
+}
-\dontrun{ # The following call requires half minute or so to execute.
+\run_dontrun{ # The following call requires half minute or so to execute.
Some warnings are issued
prsim.wave(runoff_multi_sites, "Qobs", 1, suppWarn=TRUE,
marginal="GB2")
diff --git a/PRSim/man/fun_stoch_sim_weather.Rd b/PRSim/man/fun_stoch_sim_weather.Rd
index 083c685910e850a01a1f0ca647118c778e2a1f7e..fd0ab259f6064079863b5345e87805a44e7b6061 100644
--- a/PRSim/man/fun_stoch_sim_weather.Rd
+++ b/PRSim/man/fun_stoch_sim_weather.Rd
@@ -45,12 +45,12 @@ Manuela Brunner
\examples{
data(weather_multi_sites)
-\dontrun{ # The following call requires half minute or so to execute.
+\run_dontrun{ # The following call requires half minute or so to execute.
prsim.weather(data_p=data_p, data_t=data_t, number_sim=1, p_margin='egpd',t_margin='sep')
}
-\dontrun{ # The following call requires 5 seconds to execute
+\run_dontrun{ # The following call requires 5 seconds to execute
### define normal distribution
library(fitdistrplus)
rNORM <- function(n, theta) rnorm(n, theta[1], theta[2])
diff --git a/lib/PRSim/DESCRIPTION b/lib/PRSim/DESCRIPTION
new file mode 100644
index 0000000000000000000000000000000000000000..3e35e99b9f9a42699422a16b469fa3ff153049df
--- /dev/null
+++ b/lib/PRSim/DESCRIPTION
@@ -0,0 +1,44 @@
+Package: PRSim
+Type: Package
+Title: Stochastic Simulation of Streamflow Time Series using Phase
+ Randomization
+Version: 1.4-3
+Date: 2023-06-13
+Authors@R: c(person("Manuela", "Brunner", role = c("aut", "cre"),
+ email = "manuela.brunner@env.ethz.ch",
+ comment = c(ORCID = "0000-0001-8824-877X")),
+ person("Reinhard", "Furrer", role = c("aut"),
+ email = "reinhard.furrer@math.uzh.ch",
+ comment = c(ORCID = "0000-0002-6319-2332")))
+Author: Manuela Brunner [aut, cre] (<https://orcid.org/0000-0001-8824-877X>),
+ Reinhard Furrer [aut] (<https://orcid.org/0000-0002-6319-2332>)
+Maintainer: Manuela Brunner <manuela.brunner@env.ethz.ch>
+Description: Provides a simulation framework to simulate streamflow time series with similar
+ main characteristics as observed data. These characteristics include the distribution of daily
+ streamflow values and their temporal correlation as expressed by short- and long-range
+ dependence. The approach is based on the randomization of the phases of the Fourier
+ transform or the phases of the wavelet transform. The function prsim() is applicable
+ to single site simulation and uses the Fourier transform.
+ The function prsim.wave() extends the approach to multiple sites
+ and is based on the complex wavelet transform. The function prsim.weather()
+ extends the approach to multiple variables for weather generation.
+ 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 <doi:10.5194/hess-23-3175-2019>.
+ A detailed description and evaluation of the wavelet-based multi-site approach
+ can be found in <doi:10.5194/hess-24-3967-2020>.
+ A detailed description and evaluation of the multi-variable and multi-site
+ weather generator can be found in <doi:10.5194/esd-12-621-2021>.
+URL: https://git.math.uzh.ch/reinhard.furrer/PRSim-devel
+BugReports: https://git.math.uzh.ch/reinhard.furrer/PRSim-devel/-/issues
+License: GPL-3
+Encoding: UTF-8
+LazyData: true
+Depends: R (>= 3.5.0)
+Suggests: lattice, ismev, evd, GB2, boot, MASS
+Imports: stats, methods, lmomco, mev, goftest, wavScalogram, splus2R
+RoxygenNote: 7.2.3
+Built: R 4.2.2; x86_64-w64-mingw32; 2023-06-13 07:49:59 UTC; windows
+Archs: x64
diff --git a/lib/PRSim/INDEX b/lib/PRSim/INDEX
new file mode 100644
index 0000000000000000000000000000000000000000..75adc89eda4e619c3cb77791dada0d6860a379a8
--- /dev/null
+++ b/lib/PRSim/INDEX
@@ -0,0 +1,20 @@
+PRSim-package Stochastic Simulation of Streamflow Time Series
+ using Phase Randomization
+PRsim Simulate for one station
+PRsim.wave Simulate for multiple stations
+PRsim.weather Weather simulation (temperature and
+ precipitation) for multiple stations
+runoff Sample runoff of a catchment
+runoff_multi_site_T Sample runoff and temperature data of two
+ catchments with a similar discharge regime
+runoff_multi_sites Sample runoff of four catchments with a similar
+ discharge regime
+simulations Simulated runoff
+simulations_multi_sites
+ Simulated runoff for four catchments
+weather_multi_sites Sample temperature and precipitation of four
+ catchments derived from the ERA5-Land gridded
+ dataset
+weather_sim_multi_sites
+ Simulated temperature and precipitation for two
+ grid cells
diff --git a/lib/PRSim/Meta/Rd.rds b/lib/PRSim/Meta/Rd.rds
new file mode 100644
index 0000000000000000000000000000000000000000..3b3479980f2b0e00802480d5f73af377ca9db7b7
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diff --git a/lib/PRSim/Meta/data.rds b/lib/PRSim/Meta/data.rds
new file mode 100644
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diff --git a/lib/PRSim/Meta/demo.rds b/lib/PRSim/Meta/demo.rds
new file mode 100644
index 0000000000000000000000000000000000000000..af7112ef524a94bd378bca6086a43f7ab1b7a297
Binary files /dev/null and b/lib/PRSim/Meta/demo.rds differ
diff --git a/lib/PRSim/Meta/features.rds b/lib/PRSim/Meta/features.rds
new file mode 100644
index 0000000000000000000000000000000000000000..848ce62a649aec5b5647ef7647d8f5a1318d8425
Binary files /dev/null and b/lib/PRSim/Meta/features.rds differ
diff --git a/lib/PRSim/Meta/hsearch.rds b/lib/PRSim/Meta/hsearch.rds
new file mode 100644
index 0000000000000000000000000000000000000000..fff2fb28b41731a0af645760af0c33b9aa0a53d3
Binary files /dev/null and b/lib/PRSim/Meta/hsearch.rds differ
diff --git a/lib/PRSim/Meta/links.rds b/lib/PRSim/Meta/links.rds
new file mode 100644
index 0000000000000000000000000000000000000000..f7f080b5ea6592ad625cd365c7dc474fa4991f37
Binary files /dev/null and b/lib/PRSim/Meta/links.rds differ
diff --git a/lib/PRSim/Meta/nsInfo.rds b/lib/PRSim/Meta/nsInfo.rds
new file mode 100644
index 0000000000000000000000000000000000000000..8193d81f504ea581ad933932e7a68b9d78474427
Binary files /dev/null and b/lib/PRSim/Meta/nsInfo.rds differ
diff --git a/lib/PRSim/Meta/package.rds b/lib/PRSim/Meta/package.rds
new file mode 100644
index 0000000000000000000000000000000000000000..1bd958f25c4fb0ea1ba7166e01247c7abbb5823a
Binary files /dev/null and b/lib/PRSim/Meta/package.rds differ
diff --git a/lib/PRSim/NAMESPACE b/lib/PRSim/NAMESPACE
new file mode 100644
index 0000000000000000000000000000000000000000..79f7b11e1ca6afa3eba59d1397d1fddb35d8971b
--- /dev/null
+++ b/lib/PRSim/NAMESPACE
@@ -0,0 +1,22 @@
+# importFrom("homtest", "Lmoments", "rand.kappa", "par.kappa", "F.kappa") ### make independent of homtest as homtest produces error (as of 25.3.2022)
+importFrom("stats", "rnorm", "runif", "fft",
+ "aggregate", "density", "ks.test", "lm",
+ "na.omit", "predict")
+importFrom("graphics", "hist", "abline", "lines")
+importFrom("goftest", "ad.test")
+importFrom('splus2R', 'ifelse1')
+importFrom("methods", "as")
+importFrom("stats", "deltat", "time")
+importFrom('wavScalogram', 'cwt_wst')
+importFrom('mev','fit.extgp','rextgp')
+importFrom('lmomco','lmoms','lmom2par','rlmomco')
+importFrom("stats", "optim")
+# importFrom("ismev","gev.fit")
+# importFrom("evd","rgev","pgev")
+# importFrom("GB2","mlfit.gb2","rgb2","pgb2")
+
+export("prsim")
+export("prsim.wave")
+export("prsim.weather")
+
+useDynLib(PRSim, .registration = TRUE)
diff --git a/lib/PRSim/NEWS.md b/lib/PRSim/NEWS.md
new file mode 100644
index 0000000000000000000000000000000000000000..faa5ea46c6775faded400fb2f10c1717a5dcc813
--- /dev/null
+++ b/lib/PRSim/NEWS.md
@@ -0,0 +1,15 @@
+# PRSim 1.4.3
+
+USER-VISIBLE CHANGES
+
+* added `NEWS.md` file
+
+
+
+INTERNAL CHANGES
+
+* improved repository structure, new `Makefile`.
+
+* Including example output in `tests/Examples/PRSim-Ex.Rout.save`
+
+* updated e-mail address
\ No newline at end of file
diff --git a/lib/PRSim/R/PRSim b/lib/PRSim/R/PRSim
new file mode 100644
index 0000000000000000000000000000000000000000..6686156321de4dbdb52db7e32cd99961007f56e2
--- /dev/null
+++ b/lib/PRSim/R/PRSim
@@ -0,0 +1,27 @@
+# File share/R/nspackloader.R
+# Part of the R package, https://www.R-project.org
+#
+# Copyright (C) 1995-2012 The R Core Team
+#
+# This program is free software; you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation; either version 2 of the License, or
+# (at your option) any later version.
+#
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+# GNU General Public License for more details.
+#
+# A copy of the GNU General Public License is available at
+# https://www.r-project.org/Licenses/
+
+local({
+ info <- loadingNamespaceInfo()
+ pkg <- info$pkgname
+ ns <- .getNamespace(as.name(pkg))
+ if (is.null(ns))
+ stop("cannot find namespace environment for ", pkg, domain = NA);
+ dbbase <- file.path(info$libname, pkg, "R", pkg)
+ lazyLoad(dbbase, ns, filter = function(n) n != ".__NAMESPACE__.")
+})
diff --git a/lib/PRSim/R/PRSim.rdb b/lib/PRSim/R/PRSim.rdb
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diff --git a/lib/PRSim/data/Rdata.rdb b/lib/PRSim/data/Rdata.rdb
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diff --git a/lib/PRSim/data/Rdata.rdx b/lib/PRSim/data/Rdata.rdx
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diff --git a/lib/PRSim/demo/PRSim-validate.R b/lib/PRSim/demo/PRSim-validate.R
new file mode 100644
index 0000000000000000000000000000000000000000..e299208c069fc0ca2689c3c8bf8606dd4b9f5812
--- /dev/null
+++ b/lib/PRSim/demo/PRSim-validate.R
@@ -0,0 +1,91 @@
+# short demo
+data(simulations)
+
+sim <- simulations$simulation
+
+# periodogram of deseasonalized
+kern <- kernel("modified.daniell",c(10,10))
+sp1 <- spec.pgram(sim$Qobs, k=kern, taper=0, log="no", plot=FALSE)
+sp2 <- spec.pgram(sim$des, k=kern, taper=0, log="no", plot=FALSE)
+plot(sp1, xlim=c(0,.05))
+plot( sp2, add=T, col=2)
+
+# Peaks correspond to the following cycles:
+1/sp1$freq[head(order(sp1$spec, decreasing=TRUE))]
+
+# compare periodogram of simulated series
+plot(sp1, xlim=c(0,.05)) # would be nice to identify the peaks...
+for (i in grep("r",names(sim))) {
+ spi <- spec.pgram(sim[,i], k=kern, taper=0, log="no", plot=FALSE)
+ plot( spi, add=T, col="gray")
+}
+
+sp3 <- spec.pgram(sim$Qobs, taper=0, log="no", plot=FALSE)
+1/sp3$freq[head(order(sp3$spec, decreasing=TRUE))]
+# Annual, 6 months and 4 months
+
+
+### plot mean regime for each simulation run and compare to observed regime
+### define plotting colors
+col_sim <- adjustcolor("#fd8d3c",alpha=0.8)
+col_sim_tran <- adjustcolor("#fd8d3c",alpha=0.2)
+col_obs <- adjustcolor( "black", alpha.f = 0.2)
+
+year <- unique(sim$YYYY)
+
+### compute mean runoff hydrograph
+sim$day_id <- rep(seq(1:365),times=length(year))
+mean_hydrograph_obs <- aggregate(sim$Qobs, by=list(sim$day_id), FUN=mean,simplify=FALSE)
+plot(unlist(mean_hydrograph_obs[,2]), lty=1, lwd=1, col="black", ylab=expression(paste("Discharge [m"^3,"/s]")),
+ xlab="Time [d]", main="Mean hydrographs", ylim=c(0,max(unlist(mean_hydrograph_obs[,2]))*1.5),type="l")
+
+### add mean runoff hydrographs
+for(r in 7:(length(names(sim))-1)){
+ mean_hydrograph <- aggregate(sim[,r], by=list(sim$day_id), FUN=mean,simplify=FALSE)
+ lines(mean_hydrograph, lty=1, lwd=1, col=col_sim)
+}
+### redo observed mean
+lines(mean_hydrograph_obs, lty=1, lwd=1, col="black")
+
+### autocorrelation
+acf_mare <- list()
+acf_obs <- acf(sim$Qobs, plot=FALSE)
+plot(acf_obs$acf, type="l", xlab="Lag", main="Autocorrelation", ylab="ACF")
+for(r in 7:(length(names(sim))-2)){
+ acf_sim <- acf(sim[,r], plot=FALSE)
+ lines(acf_sim$acf, col=col_sim, type="l")
+ ### compute mean relative error in the acf
+ acf_mare[[r]]<- mean(abs((acf_obs$acf-acf_sim$acf)/acf_obs$acf))
+}
+lines(acf_obs$acf)
+
+
+### partial autocorrelation function
+pacf_obs <- pacf(sim$Qobs, plot=FALSE)
+pacf_mare <- list()
+plot(pacf_obs$acf, type="l", xlab="Lag", main="Partial autocorrelation", ylab="PACF")
+for(r in 7:(length(names(sim))-2)){
+ pacf_sim <- pacf(sim[,r], plot=FALSE)
+ lines(pacf_sim$acf, col=col_sim, type="l")
+ ### compute mean relative error in the acf
+ pacf_mare[[r]] <- mean(abs((pacf_obs$acf-pacf_sim$acf)/pacf_obs$acf))
+}
+lines(pacf_obs$acf)
+
+### compute seasonal statistics
+### Q50,Q05,Q95, boxplots
+### define seasons: Winter:12,1,2; spring:3,4,5; summer: 6,7,8; fall: 9,10,11
+sim$season <- "winter"
+sim$season[which(sim$MM%in%c(3,4,5))] <- "spring"
+sim$season[which(sim$MM%in%c(6,7,8))] <- "summer"
+sim$season[which(sim$MM%in%c(9,10,11))] <- "fall"
+
+### all simulated series show the same seasonal statistics. plot only one
+boxplot(sim$Qobs[which(sim$season=="winter")], sim$r1[which(sim$season=="winter")],
+ sim$Qobs[which(sim$season=="spring")], sim$r1[which(sim$season=="spring")],
+ sim$Qobs[which(sim$season=="summer")], sim$r1[which(sim$season=="summer")],
+ sim$Qobs[which(sim$season=="fall")], sim$r1[which(sim$season=="fall")],
+ border=c("black", col_sim, "black", col_sim, "black", col_sim, "black", col_sim),
+ xaxt="n", main="Seasonal statistics", outline=FALSE)
+mtext(side=1, text=c("Winter", "Spring", "Summer", "Fall"), at=c(1.5,3.5,5.5,7.5))
+
diff --git a/lib/PRSim/demo/PRSim.R b/lib/PRSim/demo/PRSim.R
new file mode 100644
index 0000000000000000000000000000000000000000..296f1e881103c235be4acea7e6ec024dbacd2572
--- /dev/null
+++ b/lib/PRSim/demo/PRSim.R
@@ -0,0 +1,26 @@
+# short demo
+data(runoff)
+
+out <- prsim(data=runoff, number_sim=1, marginal="empirical")
+out <- prsim(data=runoff, number_sim=1, marginal="kappa", GoFtest = "KS")
+
+### GEV distribution
+require("evd")
+require("ismev")
+rGEV <- function(n, theta) rgev(n, theta[1], theta[2], theta[3])
+pGEV <- function(x, theta) pgev(x, theta[1], theta[2], theta[3])
+GEV_fit <- function( xdat, ...) gev.fit( xdat, show=FALSE, ...)$mle
+
+
+### GEV
+out <- prsim(data=runoff, number_sim=1, marginal="GEV", GoFtest = "KS", n_par=3)
+
+sim <- out$simulation
+# p_val <- out$p_val
+par(mai=c(.9,.9,.1,.1))
+plot(sim$timestamp[1:1000], sim$Qobs[1:1000], type="l",
+ xlab="Time [d]", ylab=expression(paste("Discharge [m"^3,"/s]")))
+matlines(sim$timestamp[1:1000], sim[1:1000, grep("r", names(sim))],
+ lty=1, col="gray")
+
+
diff --git a/lib/PRSim/demo/PRSim_wave-validate.R b/lib/PRSim/demo/PRSim_wave-validate.R
new file mode 100644
index 0000000000000000000000000000000000000000..e458f92866f1e8eea7124bf69b4c012b11801598
--- /dev/null
+++ b/lib/PRSim/demo/PRSim_wave-validate.R
@@ -0,0 +1,68 @@
+# short demo
+### load data for four stations
+data(simulations_multi_sites)
+sim <- simulations_multi_sites
+### loads simulations_multi_sites
+# sim <- list()
+# load("~/PRSim-devel/data/simulations_multi_sites/1_stoch_sim.rda")
+# sim[[1]] <- out_list$simulation
+# load("~/PRSim-devel/data/simulations_multi_sites/2_stoch_sim.rda")
+# sim[[2]] <- out_list$simulation
+# load("~/PRSim-devel/data/simulations_multi_sites/3_stoch_sim.rda")
+# sim[[3]] <- out_list$simulation
+# load("~/PRSim-devel/data/simulations_multi_sites/3_stoch_sim.rda")
+# sim[[4]] <- out_list$simulation
+
+# setwd("~/PRSim-devel/data")
+# save(simulations_multi_sites,file='simulations_multi_sites.rda')
+
+### define plotting colors
+col_sim <- adjustcolor("#fd8d3c",alpha=0.8)
+col_sim_tran <- adjustcolor("#fd8d3c",alpha=0.2)
+col_obs <- adjustcolor( "black", alpha.f = 0.2)
+### greys
+col_vect_obs <- c('#cccccc','#969696','#636363','#252525')
+### oranges
+col_vect_sim <- c('#fdbe85','#fd8d3c','#e6550d','#a63603')
+
+### plot time series for multiple sites
+par(mfrow=c(2,1),mar=c(3,3,2,1))
+### determine ylim
+ylim_max <- max(sim[[1]]$Qobs)*1.5
+### observed
+plot(sim[[1]]$Qobs[1:1000],ylab=expression(bold(paste("Specific discharge [mm/d]"))),xlab="Time [d]",type="l",col=col_vect_obs[1],ylim=c(0,ylim_max),main='Observations')
+for(l in 2:4){
+ lines(sim[[l]]$Qobs[1:1000],col=col_vect_obs[l])
+}
+# legend('topleft',legend=c('Station 1','Station 2','Station 3','Station 4'),lty=1,col=col_vect_obs[1:4])
+### simulated (one run)
+plot(sim[[1]]$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){
+ lines(sim[[l]]$r1[1:1000],col=col_vect_sim[l])
+}
+
+
+### plot cross-correlation function
+par(mfrow=c(4,4),mar=c(0,0,0,0))
+### run through each station comtination
+for(j in 1:4){
+ for(i in 1:4){
+ ### ccf of observations
+ data_mat <- matrix(unlist(lapply(sim, "[", , "Qobs")),ncol=length(sim))
+ ccf_obs <- ccf(data_mat[,i],data_mat[,j],plot=FALSE)
+ ### plot ccfs of observations
+ plot(ccf_obs$lag,ccf_obs$acf,col=col_obs,type="l",ylim=c(0,1),main='',xaxt='n',yaxt='n')
+
+ ### simulated ccf
+ ### run through each simulation run
+ for(r in 1:2){
+ data_mat_sim <- matrix(unlist(lapply(sim, "[", , paste("r",r,sep=""))),ncol=length(sim))
+ ccf_sim <- ccf(na.omit(cbind(data_mat_sim[,i],data_mat_sim[,j]))[,1],na.omit(cbind(data_mat_sim[,i],data_mat_sim[,j]))[,2],plot=FALSE)
+ ### add one ccf plot per simulation run
+ lines(ccf_obs$lag,ccf_sim$acf,col=col_sim)
+ }
+ ### overplot observations again
+ lines(ccf_obs$lag,ccf_obs$acf,col="black",lwd=2)
+ }
+}
+
diff --git a/lib/PRSim/demo/PRSim_wave.R b/lib/PRSim/demo/PRSim_wave.R
new file mode 100644
index 0000000000000000000000000000000000000000..bfe351cd2361e424297f714396d39554a25b5b3a
--- /dev/null
+++ b/lib/PRSim/demo/PRSim_wave.R
@@ -0,0 +1,173 @@
+###===============================###===============================###
+### Application of PRSim.wave for different (extreme value) distributions
+###===============================###===============================###
+
+### (1) Empirical distribution
+### does not allow for extrapolation to yet unobserved values
+###===============================###===============================###
+out <- prsim.wave(data=runoff_multi_sites, number_sim=1, marginal="empirical")
+
+### (2) Kappa distribution (default)
+### 4 parameters and flexible. Found to be performing best for
+### a set of 671 nearly natural catchments in the United States (Brunner and Gilleland 2020)
+###===============================###===============================###
+out <- prsim.wave(data=runoff_multi_sites, number_sim=1, marginal="kappa", GoFtest = "KS")
+# out <- prsim.wave(data=runoff_multi_sites, number_sim=5, marginal="kappa",
+# GoFtest = NULL,pars=NULL, p_val=NULL)
+# simulations_multi_sites<-list(out[[1]]$simulation,out[[2]]$simulation,out[[3]]$simulation,out[[4]]$simulation)
+# setwd("C:/Users/mbrunner/Documents/PRSim-devel/data")
+# save(simulations_multi_sites,file='simulations_multi_sites.rda')
+
+### (3) GEV distribution
+### 3 parameters, classical extreme value distribution (Coles 2001)
+###===============================###===============================###
+# require("evd")
+# require("ismev")
+# rGEV <- function(n, theta) rgev(n, theta[1], theta[2], theta[3])
+# pGEV <- function(x, theta) pgev(x, theta[1], theta[2], theta[3])
+# GEV_fit <- function( xdat, ...) gev.fit(xdat, show=FALSE, ...)$mle
+
+
+### simulate using GEV
+# out <- prsim.wave(data=runoff_multi_sites, number_sim=1, marginal="GEV", GoFtest = "KS", n_par=3)
+
+### visualize simulations
+### store stochastically simulated time series
+### station 2
+sim <- out[[2]]$simulation
+
+### plot example of simulated time series
+par(mai=c(.9,.9,.1,.1))
+### observed time series
+plot(sim$timestamp[1:1000], sim$Qobs[1:1000], type="l",
+ xlab="Time [d]", ylab=expression(paste("Discharge [m"^3,"/s]")))
+### add simulations
+matlines(sim$timestamp[1:1000], sim[1:1000, grep("r", names(sim))],
+ lty=1, col="gray")
+
+### compare distributions without outliers
+### without outliers
+boxplot(sim$Qobs,sim$r1,outline=F,col=c('black','grey'),names=c('Obs','Sim'))
+### with outliers
+boxplot(sim$Qobs,sim$r1,col=c('black','grey'),names=c('Obs','Sim'))
+
+
+### (4) generalized Beta distribution of the second kind (Mielke 1974)
+### 4 parameters: can lead to very extreme outliers, which are potentially implausible
+###===============================###===============================###
+# require( "GB2")
+# rGB2 <- function(n, theta) rgb2(n, theta[1], theta[2], theta[3], theta[4])
+# pGB2 <- function(x, theta) pgb2(x, theta[1], theta[2], theta[3], theta[4])
+# GB2_fit <- function( xdat, ...) ml.gb2( xdat, ...)$opt1$par
+#
+# ### simulate using GB2
+# out <- prsim.wave(data=runoff_multi_sites, number_sim=1, marginal="GB2", GoFtest = "KS", n_par=4)
+
+
+### (5) Normal distribution (just as a reference, will not perform well because it is not extreme)
+### 2 parameters, not flexible enough for daily flow
+###===============================###===============================###
+# library(fitdistrplus)
+# rNORM <- function(n, theta) rnorm(n, theta[1], theta[2])
+# pNORM <- function(x, theta) pnorm(x, theta[1], theta[2])
+# NORM_fit <- function( xdat, ...) fitdistr( xdat, 'normal', show=FALSE, ...)$estimate
+#
+# ### run simulations using normal distribution
+# out <- prsim.wave(data=runoff_multi_sites, number_sim=1, marginal="NORM", GoFtest = "KS", n_par=2)
+
+### (6) generalized Gamma distribution (Prentice 1974)
+### 3 parameters
+### non-stable in optimization
+###===============================###===============================###
+# library(flexsurv)
+# rGENGAM <- function(n, theta) rgengamma(n, theta[1], theta[2], theta [3])
+# pGENGAM <- function(x, theta) pgengamma(x, theta[1], theta[2], theta [3])
+# GENGAM_fit <- function( xdat, ...) fitdistr(xdat, dgengamma, start=list("mu"=0,"sigma"=0.9,"Q"=0.5))$estimate
+# ### depending on your data, it may be necessary to experiment with different start values
+# ### as optimization may produce some 'random' errors.
+# ### As optimization is not very stable, this distribution is maybe not
+# ### very useful for stochastic simulation.
+#
+# ### run simulations with generalized Gamma
+# out <- prsim.wave(data=runoff_multi_sites, number_sim=1, marginal="GENGAM", GoFtest = "KS", n_par=3)
+
+### (7) Burr type XII distribution (Burr 1942)
+### 3 parameters
+### according to my test simulations performing very poorly.
+###===============================###===============================###
+# library(actuar)
+# rBURR <- function(n, theta) rburr(n, theta[1], theta[2], theta [3])
+# pBURR <- function(x, theta) pburr(x, theta[1], theta[2], theta [3])
+# BURR_fit <- function( xdat, ...) fitdist(xdat, 'burr', start = list(shape1 = 0.3, shape2 = 0.9, rate = 0.9),method='mge')$estimate
+# ### using maximum gooness-of-fit estimation instead of maximum likelihood estimation
+# ### because the latter is numerically unstable.
+# ### run simulations with Burr type XII distribution
+# out <- prsim.wave(data=runoff_multi_sites, number_sim=1, marginal="BURR", GoFtest = "KS", n_par=3)
+
+
+### (8) Wakeby distribution (Hosking 1986)
+### 5 parameters, very flexible
+###===============================###===============================###
+# library(lmomco)
+# rWAK <- function(n, theta) rlmomco(n, list(type='wak',para=theta,source='pwarwak',ifail=0,ifailtext="Successful parameter estimation."))
+# pWAK <- function(x, theta) pdfwak(x, list(type='wak',para=theta,source='pwarwak',ifail=0,ifailtext="Successful parameter estimation."))
+# WAK_fit <- function( xdat, ...){
+# lmom_X <- lmoms(xdat)
+# ### fit Wakeby distribution
+# wakeby_X <- parwak(lmom_X)$para
+# return(wakeby_X)
+# }
+#
+# ### run simulations with Wakeby distribution
+# out <- prsim.wave(data=runoff_multi_sites, number_sim=1, marginal="WAK", GoFtest = "KS", n_par=5)
+
+### (9) Generalized Pareto
+###===============================###===============================###
+# ### produces NA values
+# rGPD <- function(n, theta) rgpd(n, theta[1], theta[2], theta[3])
+# pGPD <- function(x, theta) pgpd(x, theta[1], theta[2], theta[3])
+# GPD_fit <- function( xdat, ...){
+# param <- gpd.fit( xdat, threshold=min(xdat))
+# theta <- c(param$threshold,param$mle)
+# return(theta)
+# }
+#
+# ### run simulations with Wakeby distribution
+# out <- prsim.wave(data=runoff_multi_sites, number_sim=1, marginal="GPD", GoFtest = "KS", n_par=3)
+
+
+### (10) Lognormal distribution
+###===============================###===============================###
+# rLNORM <- function(n, theta) rlnorm(n, theta[1], theta[2])
+# pLNORM <- function(x, theta) plnorm(x, theta[1], theta[2])
+# LNORM_fit <- function( xdat, ...) fitdistr( xdat, 'lognormal', show=FALSE, ...)$estimate
+#
+# ### run simulations with Wakeby distribution
+# out <- prsim.wave(data=runoff_multi_sites, number_sim=1, marginal="LNORM", GoFtest = "KS", n_par=2)
+
+
+### (11) Generalized logistic
+### 3 parameters
+### not worth testing as it produced negative values
+###===============================###===============================###
+# library(glogis)
+# rGLOGIS <- function(n, theta) rglogis(n, theta[1], theta[2], theta[3])
+# pGLOGIS <- function(x, theta) plnorm(x, theta[1], theta[2], theta[3])
+# GLOGIS_fit <- function(xdat, ...) glogisfit(xdat)$coefficients
+#
+# ### run simulations with Wakeby distribution
+# out <- prsim.wave(data=runoff_multi_sites, number_sim=1, marginal="GLOGIS", GoFtest = "KS", n_par=3)
+
+
+### (12) Pearson type III
+###===============================###===============================###
+# library(FAdist)
+# rPEARSON <- function(n, theta) rgamma3(n, theta[1], theta[2], theta[3])
+# pPEARSON <- function(x, theta) pgamma3(x, theta[1], theta[2], theta[3])
+# PEARSON_fit <- function( xdat, ...) fitdist(xdat, 'gamma3',start=list(shape=0.9,scale=0.9,thres=mean(xdat)),method='mge')$estimate
+# ### using maximum gooness-of-fit estimation instead of maximum likelihood estimation
+# ### because the latter is numerically unstable.
+#
+# ### run simulations with Wakeby distribution
+# out <- prsim.wave(data=runoff_multi_sites, number_sim=1, marginal="PEARSON", GoFtest = "KS", n_par=3)
+
diff --git a/lib/PRSim/demo/PRSim_weather-validate.R b/lib/PRSim/demo/PRSim_weather-validate.R
new file mode 100644
index 0000000000000000000000000000000000000000..4624b9bfdb1aa4c40ab84d243e1c00bd9ba8719f
--- /dev/null
+++ b/lib/PRSim/demo/PRSim_weather-validate.R
@@ -0,0 +1,48 @@
+# short demo for prsim.weather
+### load data for four stations
+data(weather_sim_multi_sites)
+sim <- weather_sim_multi_sites
+# weather_sim_multi_sites <- list(weather_sim_multi_sites[[1]],weather_sim_multi_sites[[2]])
+# save(file='weather_sim_multi_sites.rda', weather_sim_multi_sites)
+
+### define plotting colors
+col_sim <- adjustcolor("#fd8d3c",alpha=0.8)
+col_sim_tran <- adjustcolor("#fd8d3c",alpha=0.2)
+col_obs <- adjustcolor( "black", alpha.f = 0.2)
+### greys
+col_vect_obs <- c('#cccccc','#969696','#636363','#252525')
+### oranges
+col_vect_sim <- c('#fdbe85','#fd8d3c','#e6550d','#a63603')
+
+### plot time series for multiple sites
+
+### Temperature (first list entry)
+par(mfrow=c(2,1),mar=c(3,3,2,1))
+### determine ylim
+ylim_max <- max(sim[[1]][[1]]$Temp)*1.5
+### observed
+plot(sim[[1]][[1]]$Temp[1:1000],ylab=expression(bold(paste("Temperature [degrees]"))),xlab="Time [d]",type="l",col=col_vect_obs[1],ylim=c(0,ylim_max),main='Observations')
+for(l in 2){
+ lines(sim[[l]][[1]]$Temp[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])
+### simulated (one run)
+plot(sim[[1]][[1]]$r1[1:1000],ylab=expression(bold(paste("Temperature [degrees]"))),xlab="Time [d]",type="l",col=col_vect_sim[1],ylim=c(0,ylim_max),main='Stochastic simulations')
+for(l in 2){
+ lines(sim[[l]][[1]]$r1[1:1000],col=col_vect_sim[l])
+}
+
+
+### precipitation (second list entry)
+ylim_max <- max(sim[[1]][[2]]$Prec)*1
+### observed
+plot(sim[[1]][[2]]$Prec[1:1000],ylab=expression(bold(paste("Precipitation [mm/d]"))),xlab="Time [d]",type="l",col=col_vect_obs[1],ylim=c(0,ylim_max),main='Observations')
+for(l in 2){
+ lines(sim[[l]][[2]]$Prec[1:1000],col=col_vect_obs[l])
+}
+# legend('topleft',legend=c('Station 1','Station 2','Station 3','Station 4'),lty=1,col=col_vect_obs[1:4])
+### simulated (one run)
+plot(sim[[1]][[2]]$r1[1:1000],ylab=expression(bold(paste("Precipitation [mm/d]"))),xlab="Time [d]",type="l",col=col_vect_sim[1],ylim=c(0,ylim_max),main='Stochastic simulations')
+for(l in 2){
+ lines(sim[[l]][[2]]$r1[1:1000],col=col_vect_sim[l])
+}
diff --git a/lib/PRSim/demo/PRSim_weather.R b/lib/PRSim/demo/PRSim_weather.R
new file mode 100644
index 0000000000000000000000000000000000000000..a9c83c43973f69335e0ce1c6f0b1eec55357ede3
--- /dev/null
+++ b/lib/PRSim/demo/PRSim_weather.R
@@ -0,0 +1,48 @@
+###===============================###===============================###
+### Application of PRSim.weather for temperature and precipitation
+###===============================###===============================###
+### load data for four stations
+data(weather_multi_sites) ### loads data_p and data_t
+# weather_multi_sites <- rep(list(rep(list(NA),times=2)),times=4)
+# weather_multi_sites[[1]][[1]] <- data_t[[1]]
+# weather_multi_sites[[1]][[2]] <- data_p[[1]]
+# weather_multi_sites[[2]][[1]] <- data_t[[2]]
+# weather_multi_sites[[2]][[2]] <- data_p[[2]]
+# weather_multi_sites[[3]][[1]] <- data_t[[3]]
+# weather_multi_sites[[3]][[2]] <- data_p[[3]]
+# weather_multi_sites[[4]][[1]] <- data_t[[4]]
+# weather_multi_sites[[4]][[2]] <- data_p[[4]]
+# setwd("~/PRSim-devel/data")
+# save(file='weather_multi_sites.rda',weather_multi_sites)
+
+### (1) apply function with default distributions
+### temperature: SEP, precipitation: E-GPD
+### does not allow for extrapolation to yet unobserved values
+###===============================###===============================###
+data_t <- sapply(weather_multi_sites,function(x) x[1])
+data_p <- sapply(weather_multi_sites,function(x) x[2])
+# out <- prsim.weather(data_p=data_p, data_t=data_t, number_sim=5, p_margin='egpd',t_margin='sep')
+### save example simulation data
+# weather_sim_multi_sites <- out
+# setwd("~/PRSim-devel/data")
+# save(file='weather_sim_multi_sites.rda',weather_sim_multi_sites)
+
+### (2) example with alternative distributions
+### rCDF and CDF_fit need to be defined
+### temperature: normal, precipitation: GEV
+###===============================###===============================###
+### define normal distribution
+# library(fitdistrplus)
+# rNORM <- function(n, theta) rnorm(n, theta[1], theta[2])
+# pNORM <- function(x, theta) pnorm(x, theta[1], theta[2])
+# NORM_fit <- function( xdat, ...) fitdistr(xdat, 'normal', show=FALSE, ...)$estimate
+# ### define GEV distribution
+# require("evd")
+# require("ismev")
+# rGEV <- function(n, theta) rgev(n, theta[1], theta[2], theta[3])
+# pGEV <- function(x, theta) pgev(x, theta[1], theta[2], theta[3])
+# GEV_fit <- function( xdat, ...) gev.fit(xdat, show=FALSE, ...)$mle
+#
+# ### apply function using alternative distributions
+# out <- prsim.weather(data_p=data_p, data_t=data_t, number_sim=1,p_margin='GEV',t_margin='NORM')
+# out <- prsim.weather(data_p=data_p, data_t=data_t, number_sim=1,p_margin='NORM',t_margin='NORM')
diff --git a/lib/PRSim/help/AnIndex b/lib/PRSim/help/AnIndex
new file mode 100644
index 0000000000000000000000000000000000000000..60f553feab7843f328b49aae3def8f165129c78c
--- /dev/null
+++ b/lib/PRSim/help/AnIndex
@@ -0,0 +1,22 @@
+PRSim-package PRSim-package
+PRSim PRSim-package
+PRsim fun_stoch_sim
+prsim fun_stoch_sim
+PRsim.wave fun_stoch_sim_wave
+prsim.wave fun_stoch_sim_wave
+PRsim.weather fun_stoch_sim_weather
+prsim.weather fun_stoch_sim_weather
+prsim_wave fun_stoch_sim_wave
+prsim_weather fun_stoch_sim_weather
+runoff runoff
+runoff multi site T runoff_multi_site_T
+runoff multi sites runoff_multi_sites
+runoff_multi_sites runoff_multi_sites
+runoff_multi_site_T runoff_multi_site_T
+simulations simulations
+simulations.multi.sites simulations_multi_sites
+simulations_multi_sites simulations_multi_sites
+weather multi sites weather_multi_sites
+weather.sim.multi.sites weather_sim_multi_sites
+weather_multi_sites weather_multi_sites
+weather_sim_multi_sites weather_sim_multi_sites
diff --git a/lib/PRSim/help/PRSim.rdb b/lib/PRSim/help/PRSim.rdb
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diff --git a/lib/PRSim/help/paths.rds b/lib/PRSim/help/paths.rds
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diff --git a/lib/PRSim/html/00Index.html b/lib/PRSim/html/00Index.html
new file mode 100644
index 0000000000000000000000000000000000000000..aa2199e1cd9a373a857c2eab6ef004a8b198b3da
--- /dev/null
+++ b/lib/PRSim/html/00Index.html
@@ -0,0 +1,72 @@
+<!DOCTYPE html>
+<html>
+<head><title>R: Stochastic Simulation of Streamflow Time Series using Phase
+Randomization</title>
+<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
+<meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes" />
+<link rel="stylesheet" type="text/css" href="R.css" />
+</head><body><div class="container">
+<h1> Stochastic Simulation of Streamflow Time Series using Phase
+Randomization
+<img class="toplogo" src="../../../doc/html/Rlogo.svg" alt="[R logo]" />
+</h1>
+<hr/>
+<div style="text-align: center;">
+<a href="../../../doc/html/packages.html"><img class="arrow" src="../../../doc/html/left.jpg" alt="[Up]" /></a>
+<a href="../../../doc/html/index.html"><img class="arrow" src="../../../doc/html/up.jpg" alt="[Top]" /></a>
+</div><h2>Documentation for package ‘PRSim’ version 1.4-3</h2>
+
+<ul><li><a href="../DESCRIPTION">DESCRIPTION file</a>.</li>
+<li><a href="../demo">Code demos</a>. Use <a href="../../utils/help/demo">demo()</a> to run them.</li>
+</ul>
+
+<h2>Help Pages</h2>
+
+
+<table style="width: 100%;">
+<tr><td style="width: 25%;"><a href="PRSim-package.html">PRSim-package</a></td>
+<td>Stochastic Simulation of Streamflow Time Series using Phase Randomization</td></tr>
+<tr><td style="width: 25%;"><a href="PRSim-package.html">PRSim</a></td>
+<td>Stochastic Simulation of Streamflow Time Series using Phase Randomization</td></tr>
+<tr><td style="width: 25%;"><a href="fun_stoch_sim.html">PRsim</a></td>
+<td>Simulate for one station</td></tr>
+<tr><td style="width: 25%;"><a href="fun_stoch_sim.html">prsim</a></td>
+<td>Simulate for one station</td></tr>
+<tr><td style="width: 25%;"><a href="fun_stoch_sim_wave.html">PRsim.wave</a></td>
+<td>Simulate for multiple stations</td></tr>
+<tr><td style="width: 25%;"><a href="fun_stoch_sim_wave.html">prsim.wave</a></td>
+<td>Simulate for multiple stations</td></tr>
+<tr><td style="width: 25%;"><a href="fun_stoch_sim_weather.html">PRsim.weather</a></td>
+<td>Weather simulation (temperature and precipitation) for multiple stations</td></tr>
+<tr><td style="width: 25%;"><a href="fun_stoch_sim_weather.html">prsim.weather</a></td>
+<td>Weather simulation (temperature and precipitation) for multiple stations</td></tr>
+<tr><td style="width: 25%;"><a href="fun_stoch_sim_wave.html">prsim_wave</a></td>
+<td>Simulate for multiple stations</td></tr>
+<tr><td style="width: 25%;"><a href="fun_stoch_sim_weather.html">prsim_weather</a></td>
+<td>Weather simulation (temperature and precipitation) for multiple stations</td></tr>
+<tr><td style="width: 25%;"><a href="runoff.html">runoff</a></td>
+<td>Sample runoff of a catchment</td></tr>
+<tr><td style="width: 25%;"><a href="runoff_multi_site_T.html">runoff multi site T</a></td>
+<td>Sample runoff and temperature data of two catchments with a similar discharge regime</td></tr>
+<tr><td style="width: 25%;"><a href="runoff_multi_sites.html">runoff multi sites</a></td>
+<td>Sample runoff of four catchments with a similar discharge regime</td></tr>
+<tr><td style="width: 25%;"><a href="runoff_multi_sites.html">runoff_multi_sites</a></td>
+<td>Sample runoff of four catchments with a similar discharge regime</td></tr>
+<tr><td style="width: 25%;"><a href="runoff_multi_site_T.html">runoff_multi_site_T</a></td>
+<td>Sample runoff and temperature data of two catchments with a similar discharge regime</td></tr>
+<tr><td style="width: 25%;"><a href="simulations.html">simulations</a></td>
+<td>Simulated runoff</td></tr>
+<tr><td style="width: 25%;"><a href="simulations_multi_sites.html">simulations.multi.sites</a></td>
+<td>Simulated runoff for four catchments</td></tr>
+<tr><td style="width: 25%;"><a href="simulations_multi_sites.html">simulations_multi_sites</a></td>
+<td>Simulated runoff for four catchments</td></tr>
+<tr><td style="width: 25%;"><a href="weather_multi_sites.html">weather multi sites</a></td>
+<td>Sample temperature and precipitation of four catchments derived from the ERA5-Land gridded dataset</td></tr>
+<tr><td style="width: 25%;"><a href="weather_sim_multi_sites.html">weather.sim.multi.sites</a></td>
+<td>Simulated temperature and precipitation for two grid cells</td></tr>
+<tr><td style="width: 25%;"><a href="weather_multi_sites.html">weather_multi_sites</a></td>
+<td>Sample temperature and precipitation of four catchments derived from the ERA5-Land gridded dataset</td></tr>
+<tr><td style="width: 25%;"><a href="weather_sim_multi_sites.html">weather_sim_multi_sites</a></td>
+<td>Simulated temperature and precipitation for two grid cells</td></tr>
+</table>
+</div></body></html>
diff --git a/lib/PRSim/html/R.css b/lib/PRSim/html/R.css
new file mode 100644
index 0000000000000000000000000000000000000000..2ef6cd60930e9e3a8ceaeba27764a8778e95f463
--- /dev/null
+++ b/lib/PRSim/html/R.css
@@ -0,0 +1,120 @@
+@media screen {
+ .container {
+ padding-right: 10px;
+ padding-left: 10px;
+ margin-right: auto;
+ margin-left: auto;
+ max-width: 900px;
+ }
+}
+
+.rimage img { /* from knitr - for examples and demos */
+ width: 96%;
+ margin-left: 2%;
+}
+
+.katex { font-size: 1.1em; }
+
+code {
+ color: inherit;
+ background: inherit;
+}
+
+body {
+ line-height: 1.4;
+ background: white;
+ color: black;
+}
+
+a:link {
+ background: white;
+ color: blue;
+}
+
+a:visited {
+ background: white;
+ color: rgb(50%, 0%, 50%);
+}
+
+h1 {
+ background: white;
+ color: rgb(55%, 55%, 55%);
+ font-family: monospace;
+ font-size: 1.4em; /* x-large; */
+ text-align: center;
+}
+
+h2 {
+ background: white;
+ color: rgb(40%, 40%, 40%);
+ font-family: monospace;
+ font-size: 1.2em; /* large; */
+ text-align: center;
+}
+
+h3 {
+ background: white;
+ color: rgb(40%, 40%, 40%);
+ font-family: monospace;
+ font-size: 1.2em; /* large; */
+}
+
+h4 {
+ background: white;
+ color: rgb(40%, 40%, 40%);
+ font-family: monospace;
+ font-style: italic;
+ font-size: 1.2em; /* large; */
+}
+
+h5 {
+ background: white;
+ color: rgb(40%, 40%, 40%);
+ font-family: monospace;
+}
+
+h6 {
+ background: white;
+ color: rgb(40%, 40%, 40%);
+ font-family: monospace;
+ font-style: italic;
+}
+
+img.toplogo {
+ width: 4em;
+ vertical-align: middle;
+}
+
+img.arrow {
+ width: 30px;
+ height: 30px;
+ border: 0;
+}
+
+span.acronym {
+ font-size: small;
+}
+
+span.env {
+ font-family: monospace;
+}
+
+span.file {
+ font-family: monospace;
+}
+
+span.option{
+ font-family: monospace;
+}
+
+span.pkg {
+ font-weight: bold;
+}
+
+span.samp{
+ font-family: monospace;
+}
+
+div.vignettes a:hover {
+ background: rgb(85%, 85%, 85%);
+}
diff --git a/lib/PRSim/libs/x64/PRSim.dll b/lib/PRSim/libs/x64/PRSim.dll
new file mode 100644
index 0000000000000000000000000000000000000000..42b0524473ed064c9805d407a583247f361100d2
Binary files /dev/null and b/lib/PRSim/libs/x64/PRSim.dll differ