R Under development (unstable) (2024-02-26 r85990 ucrt) -- "Unsuffered Consequences"
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> #####################
> # All of the checks in this tests subdirectory were previously run with the
> # following commented code.
> 
> # require("mva"); require("ts"); require("dse") 
> # #x11()
> #   postscript(file="lite.out.ps",  paper="letter", horizontal=F, onefile=T)
> #              # width=6, height=8, pointsize=10,
> #    system.info()
> #    DSEversion()
> #    random.number.test() 
> #    dse.function.tests(verbose=T)    
> #    example.verify.data(eg1.DSE.data.diff, fuzz.small=1e-12, verbose=T)  
> # # The following gave several..NOT CORRECT in R. It needs estVARXar (not in earlier versions of R).
> # # example.tests(eg1.DSE.data.diff,fuzz.small=1e-12, verbose=TRUE)
> 
> #####################
>  Sys.getenv("R_LIBS")
[1] "D:\\temp\\RtmpSiT7bA\\RLIBS_308482ef76f4"
>  library()
>  
>  require("dse")
Loading required package: dse
Loading required package: tfplot
Loading required package: tframe

Attaching package: 'dse'

The following objects are masked from 'package:stats':

    acf, simulate

>  search()
 [1] ".GlobalEnv"        "package:dse"       "package:tfplot"   
 [4] "package:tframe"    "package:stats"     "package:graphics" 
 [7] "package:grDevices" "package:utils"     "package:datasets" 
[10] "package:methods"   "Autoloads"         "package:base"     
> 
>  Sys.info()
       sysname        release        version       nodename        machine 
     "Windows"   "Server x64"  "build 20348"     "CRANWIN3"       "x86-64" 
         login           user effective_user 
        "CRAN"         "CRAN"         "CRAN" 
>  DSEversion()
       setRNG        tframe           dse 
   "2024.2-1" "2015.12-1.1"    "2024.2-2" 
>  data("eg1.DSE.data.diff", package="dse") 
> 
>  if (!is.TSdata(eg1.DSE.data.diff)) stop("Test data not found. Testing stopped.")
>  
> fuzz.small <- 1e-14
> fuzz.large <- 1e-10
> digits <- 18
> all.ok <- TRUE  
> 
> 
> test.rng <- list(kind="Wichmann-Hill",seed=c(979,1479,1542),normal.kind="Box-Muller")
> 
>   setRNG::random.number.test()
Random number generator tests ...ok
Warning messages:
1: In RNGkind(kind = kind, normal.kind = normal.kind) :
  RNGkind: Marsaglia-Multicarry has poor statistical properties
2: In RNGkind(kind = kind, normal.kind = normal.kind) :
  RNGkind: severe deviations from normality for Kinderman-Ramage + Marsaglia-Multicarry
3: In RNGkind(kind = kind, normal.kind = normal.kind) :
  RNGkind: Marsaglia-Multicarry has poor statistical properties
4: In RNGkind(kind = kind, normal.kind = normal.kind) :
  RNGkind: severe deviations from normality for Kinderman-Ramage + Marsaglia-Multicarry
5: In RNGkind(kind = kind, normal.kind = normal.kind) :
  buggy version of Kinderman-Ramage generator used
6: In RNGkind(kind = kind, normal.kind = normal.kind) :
  RNGkind: Marsaglia-Multicarry has poor statistical properties
> 
> 
>  cat("dse test 0 ...\n")
dse test 0 ...
>   # check "window"
>   z <- tfwindow(outputData(eg1.DSE.data.diff), start=c(1980,1), end=c(1980,1))
>   ok <- all( c (c(1,3)==dim(z), c(1980,1)==start(z), c(1980,1)==end(z)))
>   z <- tfwindow(outputData(eg1.DSE.data.diff), start=c(1980,1), end=c(1982,12))
>   ok <- ok & all( c (c(36,3)==dim(z), c(1980,1)==start(z), c(1982,12)==end(z)))
>   all.ok <- ok
> 
> 
>  cat("dse test 1 ...\n")
dse test 1 ...
>   z <- estVARXls(eg1.DSE.data.diff)
> #  z <-eg1.DSE.data.diff
> #  lsfit produces warning messages in the following
> #  z$output[100,] <-NA
> #  z <- estVARXls(z, warn=F)
>   VARmodel  <-  estVARXar(eg1.DSE.data.diff, re.add.means=FALSE, warn=FALSE)
>   SSmodel  <- toSS(VARmodel)
>   ok <- fuzz.large > abs(VARmodel$estimates$like[1] -
+                l(SSmodel, eg1.DSE.data.diff, warn=FALSE)$estimates$like[1])
>   ok <- ok & is.TSestModel(VARmodel) & is.TSmodel(VARmodel$model)
>   ok <- ok & (nseriesInput(VARmodel) == nseriesInput(SSmodel))
>   ok <- ok & (nseriesInput(VARmodel) == nseriesInput(VARmodel$data))
>   ok <- ok & (nseriesOutput(VARmodel) == nseriesOutput(SSmodel))
>   ok <- ok & (nseriesOutput(VARmodel) == nseriesOutput(VARmodel$data))
>   VARmodelB <- TSmodel(VARmodel)
>   B <- t(chol(VARmodel$estimates$cov))
>   VARmodelB$B <- array(B, c(1,dim(B)))  # has B != I
>   VARmodelB <- setTSmodelParameters(VARmodelB)
>   VARmodelB <- l(VARmodelB,VARmodel$data, warn=FALSE)
> 
>   z <- residuals(VARmodelB)
>   z <- acf(VARmodelB)
>   #x11()
>   #get(getOption("device"))()
>   dev.new()
dev.new(): using pdf(file="Rplots1.pdf")
>   acf(VARmodelB)
> 
>    good <- VARmodel$estimates$pred
>    tst  <- VARmodelB$estimates$pred
>    error <- max(abs(good-tst))
>    cat("max. error ", max(error))
max. error  2.081668e-17> 
>    if (any(is.na(error)) || any(is.nan(error)) || fuzz.large < error) 
+      {printTestValue(c(tst), digits=18)
+       all.ok <- FALSE  
+      }
> 
>   if (! all.ok) stop("some tests FAILED")
> 
> 
> proc.time()
   user  system elapsed 
   0.40    0.09    0.48