Nothing
#####################
# 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")
library()
require("dse")
search()
Sys.info()
DSEversion()
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()
cat("dse test 0 ...\n")
# 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")
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()
acf(VARmodelB)
good <- VARmodel$estimates$pred
tst <- VARmodelB$estimates$pred
error <- max(abs(good-tst))
cat("max. error ", max(error))
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")
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