* using log directory ‘/data/gannet/ripley/R/packages/tests-LENGTH1/PRSim.Rcheck’
* using R Under development (unstable) (2022-04-03 r82074)
* using platform: x86_64-pc-linux-gnu (64-bit)
* using session charset: UTF-8
* using option ‘--no-stop-on-test-error’
* checking for file ‘PRSim/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘PRSim’ version ‘1.4-1’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for executable files ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘PRSim’ can be installed ... [11s/11s] OK
* checking package directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking use of S3 registration ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... [15s/15s] OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd line widths ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking LazyData ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking pragmas in C/C++ headers and code ... OK
* checking compilation flags used ... OK
* checking compiled code ... OK
* checking examples ... OK
* checking differences from ‘PRSim-Ex.Rout’ to ‘PRSim-Ex.Rout.save’ ... OK

23,24d22
< > ##D demo("PRSim_weather")
< > ##D demo("PRSim_weather-validate")
55c53
< This is mgcv 1.8-40. For overview type 'help("mgcv-package")'.
---
> This is mgcv 1.8-31. For overview type 'help("mgcv-package")'.
111c109
< This is mgcv 1.8-40. For overview type 'help("mgcv-package")'.
---
> This is mgcv 1.8-31. For overview type 'help("mgcv-package")'.
146,187d143
< > nameEx("fun_stoch_sim_weather")
< > ### * fun_stoch_sim_weather
< > 
< > flush(stderr()); flush(stdout())
< > 
< > ### Name: pRsim.weather
< > ### Title: Weather simulation (temperature and precipitation) for multiple
< > ###   stations
< > ### Aliases: PRsim.weather prsim.weather prsim_weather
< > ### Keywords: ts
< > 
< > ### ** Examples
< > 
< > data(weather_multi_sites)
< > ## Not run: 
< > ##D  # The following call requires half minute or so to execute. 
< > ##D prsim.weather(data_p=data_p, data_t=data_t, number_sim=1, p_margin='egpd',t_margin='sep')
< > ## End(Not run)
< > 
< > 
< > ## Not run: 
< > ##D  # The following call requires 5 seconds to execute
< > ##D ### define normal distribution
< > ##D library(fitdistrplus)
< > ##D rNORM <- function(n, theta)  rnorm(n, theta[1], theta[2])
< > ##D pNORM <- function(x, theta)  pnorm(x, theta[1], theta[2])
< > ##D NORM_fit <- function( xdat, ...)   fitdistr( xdat, 'normal', show=FALSE, ...)$estimate
< > ##D ### define GEV distribution
< > ##D require("evd")
< > ##D require("ismev")
< > ##D rGEV <- function(n, theta)  rgev(n, theta[1], theta[2], theta[3])
< > ##D pGEV <- function(x, theta)  pgev(x, theta[1], theta[2], theta[3])
< > ##D GEV_fit <- function( xdat, ...)   gev.fit(xdat, show=FALSE, ...)$mle
< > ##D 
< > ##D ### apply function using alternative distributions
< > ##D out <- prsim.weather(data_p=data_p, data_t=data_t, number_sim=1,p_margin='GEV',t_margin='NORM')
< > ## End(Not run)
< > 
< > 
< > 
< > 
< > cleanEx()
216,253d171
< > nameEx("runoff_multi_site_T")
< > ### * runoff_multi_site_T
< > 
< > flush(stderr()); flush(stdout())
< > 
< > ### Name: runoff_multi_site_T
< > ### Title: Sample runoff and temperature data of two catchments with a
< > ###   similar discharge regime
< > ### Aliases: runoff_multi_site_T 'runoff multi site T'
< > ### Keywords: datasets
< > 
< > ### ** Examples
< > 
< > data(runoff_multi_site_T)
< > str(runoff_multi_site_T) 
< List of 2
<  $ :'data.frame':	11323 obs. of  5 variables:
<   ..$ YYYY: chr [1:11323] "1980" "1980" "1980" "1980" ...
<   ..$ MM  : chr [1:11323] "01" "01" "01" "01" ...
<   ..$ DD  : chr [1:11323] "01" "02" "03" "04" ...
<   ..$ Qobs: num [1:11323] 31.4 29.1 28.5 27.7 38.4 ...
<   ..$ T   : num [1:11323] -3.372 -4.512 -4.938 -2.783 0.421 ...
<  $ :'data.frame':	11323 obs. of  5 variables:
<   ..$ YYYY: chr [1:11323] "1980" "1980" "1980" "1980" ...
<   ..$ MM  : chr [1:11323] "01" "01" "01" "01" ...
<   ..$ DD  : chr [1:11323] "01" "02" "03" "04" ...
<   ..$ Qobs: num [1:11323] 0.2 0.16 0.17 0.17 0.16 0.15 0.15 0.14 0.14 0.13 ...
<   ..$ T   : num [1:11323] -9.89 -11.27 -11.47 -7.39 -2.75 ...
< > runoff_multi_site_T[[1]]$timestamp <- paste(runoff_multi_site_T[[1]]$YYYY, 
< + runoff_multi_site_T[[1]]$MM, runoff_multi_site_T[[1]]$DD, sep=" ")
< > runoff_multi_site_T[[1]]$timestamp <- 
< + as.POSIXct(strptime(runoff_multi_site_T[[1]]$timestamp,format="%Y %m %d", tz="GMT"))
< > plot(runoff_multi_site_T[[1]]$timestamp[1:1000], runoff_multi_site_T[[1]]$Qobs[1:1000], type="l", 
< +   xlab="Time [d]", ylab=expression(paste("Discharge [m"^3,"/s]")))
< > 
< > 
< > 
< > cleanEx()
316c234
< [1] 6570   11
---
> [1] 6570   56
375,474d292
< + }
< > 
< > 
< > 
< > graphics::par(get("par.postscript", pos = 'CheckExEnv'))
< > cleanEx()
< > nameEx("weather_multi_sites")
< > ### * weather_multi_sites
< > 
< > flush(stderr()); flush(stdout())
< > 
< > ### Name: weather_multi_sites
< > ### Title: Sample temperature and precipitation of four catchments derived
< > ###   from the ERA5-Land gridded dataset
< > ### Aliases: weather_multi_sites 'weather multi sites'
< > ### Keywords: datasets
< > 
< > ### ** Examples
< > 
< > data(weather_multi_sites)
< > weather_multi_sites[[1]][[1]]$timestamp <- paste(weather_multi_sites[[1]][[1]]$YYYY, 
< + weather_multi_sites[[1]][[1]]$MM, weather_multi_sites[[1]][[1]]$DD, sep=" ")
< > weather_multi_sites[[1]][[1]]$timestamp <- 
< + as.POSIXct(strptime(weather_multi_sites[[1]][[1]]$timestamp,
< + format="%Y %m %d", tz="GMT"))
< > plot(weather_multi_sites[[1]][[1]]$timestamp[1:1000],
< + weather_multi_sites[[1]][[1]]$Qobs[1:1000], type="l", 
< + xlab="Time [d]", ylab=expression(paste("Temperature [degrees]")))
< > 
< > 
< > 
< > cleanEx()
< > nameEx("weather_sim_multi_sites")
< > ### * weather_sim_multi_sites
< > 
< > flush(stderr()); flush(stdout())
< > 
< > ### Name: weather_sim_multi_sites
< > ### Title: Simulated temperature and precipitation for two grid cells
< > ### Aliases: weather.sim.multi.sites weather_sim_multi_sites
< > ### Keywords: datasets
< > 
< > ### ** Examples
< > 
< > data(weather_sim_multi_sites)
< > sim <- 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]]$Temp[1:1000],col=col_vect_obs[l])
< + }
< > # legend('topleft',legend=c('Station 1','Station 2'
< > # ),lty=1,col=col_vect_obs[1:2])
< > ### simulated (one run)
< > plot(sim[[1]][[1]]$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'
< > # ),lty=1,col=col_vect_obs[1:2])
< > ### 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])
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘basic.R’ [32s/32s]
 [33s/33s] ERROR
Running the tests in ‘tests/basic.R’ failed.
Complete output:
  > # some simple testing commands...
  > #   testthat would be an overshoot...
  > 
  > require(PRSim)
  Loading required package: PRSim
  > 
  > # raw demos
  > demo( "PRSim", ask=FALSE)
  
  
  	demo(PRSim)
  	---- ~~~~~
  
  > # short demo
  > data(runoff)
  
  > out <- prsim(data=runoff, number_sim=1, marginal="empirical")
  Detrending with (half-)length 15...
  Starting 1 simulations:
  .
  Finished.
  
  > out <- prsim(data=runoff, number_sim=1, marginal="kappa", GoFtest = "KS")
  Detrending with (half-)length 15...
  Starting 1 simulations:
  .
  Finished.
  
  > ### GEV distribution
  > require("evd")
  Loading required package: evd
  
  > require("ismev")
  Loading required package: ismev
  Loading required package: mgcv
  Loading required package: nlme
  This is mgcv 1.8-40. For overview type 'help("mgcv-package")'.
  
  > 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)
  Detrending with (half-)length 15...
  Starting 1 simulations:
  .
  Finished.
  
  > 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")
  > demo( "PRSim-validate", ask=FALSE)
  
  
  	demo(PRSim-validate)
  	---- ~~~~~~~~~~~~~~
  
  > # 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))]
  [1] 355.2632 375.0000 337.5000 321.4286 397.0588 306.8182
  
  > # 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))]
  [1] 375.0000 355.2632 182.4324 122.7273 337.5000 421.8750
  
  > # 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))
  > 
  > 
  > 
  > # testing input
  > data(runoff)
  > unique(runoff$YYYY)
   [1] 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989
  [16] 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
  [31] 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
  > 
  > 
  > try( prsim( runoff[1:130,] ))   #  At least one year of data required.
  Error in prsim(runoff[1:130, ]) : At least one year of data required.
  > try( prsim( runoff[1:730,] ))   #  No missing values allowed. Some days are missing.
  Error in prsim(runoff[1:730, ]) : 
    No missing values allowed. Some days are missing.
  > try( prsim( runoff[1:1445,] ))  #  No missing values allowed. Some days are missing.
  Error in prsim(runoff[1:1445, ]) : 
    No missing values allowed. Some days are missing.
  > try( prsim( runoff[runoff$YYYY<1976,] )) # At least one year of data required.
  Error in prsim(runoff[runoff$YYYY < 1976, ]) : 
    At least one year of data required.
  > 
  > 
  > 
  > suppressWarnings( out <- prsim( runoff[runoff$YYYY<1977,] ) )
  Detrending with (half-)length 15...
  Starting 1 simulations:
  .
  Finished.
  > 
  > runof <- runoff[runoff$YYYY<1980,]
  > 
  > set.seed(1)
  > str(out1 <- prsim( runof, marginalpar=FALSE, suppWarn=TRUE))
  Detrending with (half-)length 15...
  Starting 1 simulations:
  .
  Finished.
  List of 3
   $ simulation:'data.frame':	1825 obs. of  7 variables:
    ..$ YYYY         : int [1:1825] 1975 1975 1975 1975 1975 1975 1975 1975 1975 1975 ...
    ..$ MM           : int [1:1825] 1 1 1 1 1 1 1 1 1 1 ...
    ..$ DD           : int [1:1825] 1 2 3 4 5 6 7 8 9 10 ...
    ..$ timestamp    : POSIXct[1:1825], format: "1975-01-01" "1975-01-02" ...
    ..$ Qobs         : num [1:1825] 2.05 1.75 1.62 1.58 1.47 ...
    ..$ deseaonalized: num [1:1825] 1.595 0.738 1.512 0.944 0.919 ...
    ..$ r1           : num [1:1825] 0.812 0.665 0.449 0.842 0.928 ...
   $ pars      : NULL
   $ p_val     : NULL
  > 
  > runo <- runof
  > names( runo) <- tolower( names(runof))
  > try( prsim( runo, marginalpar=FALSE, suppWarn=TRUE)) #  Wrong column for observations selected.
  Error in prsim(runo, marginalpar = FALSE, suppWarn = TRUE) : 
    Wrong column (name) for observations selected.
  > 
  > runo <- runof[,4:1]
  > set.seed(1)
  > out3 <- prsim( runo, marginalpar=FALSE, suppWarn=TRUE) #  ok
  Detrending with (half-)length 15...
  Starting 1 simulations:
  .
  Finished.
  > identical(out1,out3) 
  [1] TRUE
  > 
  > runo <- runof[,4:1]
  > set.seed(1)
  > out4 <- prsim( runo, station_id=1, marginalpar=FALSE, suppWarn=TRUE) #  ok
  Detrending with (half-)length 15...
  Starting 1 simulations:
  .
  Finished.
  > identical(out1,out4) 
  [1] TRUE
  > 
  > tmp <- paste(runof$YYYY, runof$MM, runof$DD,sep=" ")
  > runo <- data.frame(time=as.POSIXct(strptime(tmp, format="%Y %m %d", tz="GMT")), Qobs=runof$Qobs)
  > set.seed(1)
  > out5 <- prsim( runo, marginalpar=FALSE, suppWarn=TRUE) #  ok
  Detrending with (half-)length 15...
  Starting 1 simulations:
  .
  Finished.
  > identical(out1,out5) 
  [1] TRUE
  > 
  > # 
  > 
  > ######################
  > # Test 'kappa' distribution with manual construction:
  > rKappa <- function(n, theta) homtest::rand.kappa(n, theta[1], theta[2], theta[3], theta[4])
  > Kappa_fit <- function(xdat, ...) {
  +   ll <- homtest::Lmoments(xdat)  
  +   unlist(homtest::par.kappa(ll[1],ll[2],ll[4],ll[5]))
  + }
  > set.seed(1)
  > out6a <- prsim( runo, marginalpar=TRUE)
  Detrending with (half-)length 15...
  Starting 1 simulations:
  .
  Finished.
  > set.seed(1)
  > out6b <- prsim( runo, marginal="Kappa", marginalpar=TRUE)
  Detrending with (half-)length 15...
   ----------- FAILURE REPORT -------------- 
   --- failure: length > 1 in coercion to logical ---
   --- srcref --- 
  : 
   --- package (from environment) --- 
  homtest
   --- call from context --- 
  invF.kappa(F, xi, alfa, k, h)
   --- call from argument --- 
  (F < 0) || (F > 1)
   --- R stacktrace ---
  where 1: invF.kappa(F, xi, alfa, k, h)
  where 2: homtest::rand.kappa(n, theta[1], theta[2], theta[3], theta[4])
  where 3: rCDF(n = length(data_window), theta)
  where 4: prsim(runo, marginal = "Kappa", marginalpar = TRUE)
  
   --- value of length: 150 type: logical ---
    [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
   [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
   [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
   [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
   [49] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
   [61] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
   [73] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
   [85] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
   [97] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [109] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [121] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [133] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [145] FALSE FALSE FALSE FALSE FALSE FALSE
   --- function from context --- 
  function (F, xi, alfa, k, h) 
  {
      if ((F < 0) || (F > 1)) {
          stop("F must be between 0 and 1")
      }
      if (k == 0) {
          k <- 10^(-100)
      }
      if (h == 0) {
          x <- invF.GEV(F, xi, alfa, k)
      }
      else {
          x <- xi + (alfa/k) * (1 - ((1 - F^h)/h)^k)
      }
      return(x)
  }
  <bytecode: 0xe38fe08>
  <environment: namespace:homtest>
   --- function search by body ---
  Function invF.kappa in namespace homtest has this body.
   ----------- END OF FAILURE REPORT -------------- 
  Fatal error: length > 1 in coercion to logical
* checking PDF version of manual ... OK
* checking for non-standard things in the check directory ... OK
* checking for detritus in the temp directory ... OK
* DONE

Status: 1 ERROR
See
  ‘/data/gannet/ripley/R/packages/tests-LENGTH1/PRSim.Rcheck/00check.log’
for details.

Command exited with non-zero status 1
Time 1:52.88, 104.27 + 7.94