Last updated on 2025-12-07 04:50:10 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.0-13 | 5.46 | 77.25 | 82.71 | OK | |
| r-devel-linux-x86_64-debian-gcc | 1.0-13 | 4.56 | 54.24 | 58.80 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 1.0-13 | 27.00 | 105.35 | 132.35 | OK | |
| r-devel-linux-x86_64-fedora-gcc | 1.0-13 | 13.00 | 106.28 | 119.28 | OK | |
| r-devel-windows-x86_64 | 1.0-13 | 7.00 | 106.00 | 113.00 | OK | |
| r-patched-linux-x86_64 | 1.0-13 | 5.98 | 70.53 | 76.51 | OK | |
| r-release-linux-x86_64 | 1.0-13 | 4.77 | 70.05 | 74.82 | OK | |
| r-release-macos-arm64 | 1.0-13 | OK | ||||
| r-release-macos-x86_64 | 1.0-13 | 4.00 | 102.00 | 106.00 | OK | |
| r-release-windows-x86_64 | 1.0-13 | 7.00 | 104.00 | 111.00 | OK | |
| r-oldrel-macos-arm64 | 1.0-13 | NOTE | ||||
| r-oldrel-macos-x86_64 | 1.0-13 | 5.00 | 100.00 | 105.00 | NOTE | |
| r-oldrel-windows-x86_64 | 1.0-13 | 10.00 | 132.00 | 142.00 | OK |
Version: 1.0-13
Check: tests
Result: ERROR
Running ‘doExtras.R’ [0s/0s]
Comparing ‘doExtras.Rout’ to ‘doExtras.Rout.save’ ... OK
Running ‘getArray-swap.R’ [1s/1s]
Running ‘tst-wrongs.R’ [18s/42s]
Running ‘tstTGforecasts.R’ [0s/1s]
Running ‘tstVaRsuperadd.R’ [3s/10s]
Running ‘varlist.R’ [1s/1s]
Running the tests in ‘tests/tstTGforecasts.R’ failed.
Complete output:
> #### A "fast" and simplified version of demo(TGforecasts)
> #### see ../demo/TGforecasts.R
> #### ~~~~~~~~~~~~~~~~~~~~~
>
> require(simsalapar)
Loading required package: simsalapar
> ## also require(fGarch)
>
>
> ### Variable list ##############################################################
>
> ## Create varlist (default type is 'frozen'; default expressions are generated)
> ## note: no n.sim here
> vList <-
+ varlist(forecaster = list(type="grid", expr = quote(italic(forecaster)),
+ value = c("statistician", "optimist", "pessimist")),
+ scoringfun = list(type="inner", expr = quote(S),
+ value = list(SE = function(x, y) mean((x-y)^2),
+ AE = function(x, y) mean(abs(x-y)))),
+ ## GARCH(1,1): X_t = sigma_t * eps_t,
+ ## sigma_t^2 = alpha_0 + alpha_1*X_{t-1}^2 + beta_1*sigma_{t-1}^2
+ alpha0 = list(expr = quote(alpha[0]), value = 0.05),
+ alpha1 = list(expr = quote(alpha[1]), value = 0.2),
+ beta1 = list(expr = quote(beta[1]), value = 0.75),
+ ## constant prediction of optimist:
+ pred.optimist = list(expr = "Optimist", value = 5),
+ ## constant prediction of pessimist:
+ pred.pessimist = list(expr = "Pessimist", value = 0.05),
+ ## n
+ n = list(value = 64),
+ ## simulation method
+ method = list(value = "fGarch"))
>
> ### doOne() including ingredient functions #####################################
> ## -------
> ## instead of 'local', use a construction like
> ## doOne <- function(x, <nonGrids>, simGARCH11, predictTG)
>
> doOne <- local({
+
+ ## function for simulating a squared GARCH(1,1)
+ simGARCH11 <- function(n, a0, a1, b1, method=c("fGarch", "Gneiting"))
+ {
+ method <- match.arg(method)
+ switch(method,
+ "fGarch" = {
+ ## specify the GARCH(1,1) process
+ spec <- fGarch::garchSpec(model =
+ list(omega = a0, alpha = a1, beta = b1))
+ ## simulate; extended=TRUE => data.frame
+ ## with columns garch, sigma, eps time series
+ fGarch::garchSim(spec, n=n, extended=TRUE)
+ },
+ "Gneiting" = { # Gneiting's code (with minor adjustments)
+ alpha <- a1
+ beta <- b1
+ gamma <- a0
+ z <- rep(0, n+1)
+ y <- rep(0, n+1)
+ sigmasq <- rep(1, n+1)
+ z[1] <- rnorm(1)
+ for (t in 2:(n+1)) {
+ sigmasq[t] <- alpha*z[t-1]^2 + beta*sigmasq[t-1] + gamma
+ z[t] <- rnorm(1, sd=sqrt(sigmasq[t]))
+ }
+ ts(cbind(garch=z[-1], sigma=sqrt(sigmasq[-1])))
+ },
+ stop("wrong 'method'"))
+ }
+
+ ## prediction function
+ predictTG <- function(x, n, forecaster, pred.opt, pred.pes) {
+ stopifnot(is.character(forecaster))
+ switch(forecaster,
+ "optimist" = rep(pred.opt, n),
+ "pessimist" = rep(pred.pes, n),
+ ## statistician predicts hat{X}_t = E[Y_t | sigma_t^2] = sigma_t^2
+ "statistician" = x[,"sigma"]^2,
+ stop("forecaster not supported"))
+ }
+
+ ##' Statistic (use it like this to include simulation in time measurement)
+
+ ##' @title Function to Compute the Simulation Results for One Grid Line
+ ##' @param x one-line data.frame containing a combination of grid variables
+ ##' @param nonGrids values of non-"grid"-variables
+ ##' @return return value of doCallWE()
+ ##' @author Marius Hofert
+ function(n, alpha0, alpha1, beta1, forecaster,
+ pred.optimist, pred.pessimist, method, scoringfun)
+ {
+ ## simulate squared GARCH(1,1)
+ X <- simGARCH11(n, a0=alpha0, a1=alpha1, b1=beta1, method=method)
+ Y <- X[,"garch"]^2 # see (2) in Gneiting (2011)
+ ## predict
+ pred <- predictTG(X, n=n, forecaster=forecaster,
+ pred.opt=pred.optimist, pred.pes=pred.pessimist)
+
+ ## basic check
+ stopifnot(length(pred)==length(Y))
+
+ ## compute scoring functions (for all 'inner' variables simultaneously)
+ c(SE = scoringfun[["SE"]](pred, y=Y),
+ AE = scoringfun[["AE"]](pred, y=Y))
+ }
+ })
>
> ## build grid and non-grid variables
> stopifnot(dim(pGrid <- mkGrid(vList)) == c(3,1), # only the forecaster here
+ get.nonGrids(vList)$n.sim == 1) # the "automatic n.sim" if there is none
>
> tex.vl <- toLatex(vList)
>
> ### Computation ################################################################
>
> S.T <- system.time
>
> ## 'reproducing' Table 4 in Gneiting (2011)
>
> ## sequentially
> S.T(res <- doLapply(vList, doOne=doOne, monitor=TRUE))
Error in doCheck(doOne, vList, nChks = 1, verbose = FALSE) :
is.numeric(r) is not TRUE
Calls: S.T -> doLapply -> doCheck -> stopifnot
Timing stopped at: 0.004 0 0.004
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 1.0-13
Check: package dependencies
Result: NOTE
Package suggested but not available for checking: ‘Rmpi’
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64
Version: 1.0-13
Check: Rd cross-references
Result: NOTE
Package unavailable to check Rd xrefs: ‘Rmpi’
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64