Running examples in ‘surveillance-Ex.R’ failed
The error most likely occurred in:

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: hhh4_simulate
> ### Title: Simulate '"hhh4"' Count Time Series
> ### Aliases: simulate.hhh4
> ### Keywords: datagen
> 
> ### ** Examples
> 
> data(influMen)
> # convert to sts class and extract meningococcal disease time series
> meningo <- disProg2sts(influMen)[,2]
> 
> # fit model
> fit <- hhh4(meningo, control = list(
+               ar = list(f = ~ 1),
+               end = list(f = addSeason2formula(~1, period = 52)),
+               family = "NegBin1"))
> plot(fit)
> 
> # simulate from model (generates an "sts" object)
> simData <- simulate(fit, seed=1234)
> 
> # plot simulated data
> plot(simData, main = "simulated data", xaxis.labelFormat=NULL)
> 
> # use simplify=TRUE to return an array of simulated counts
> simCounts <- simulate(fit, seed=1234, simplify=TRUE)
> dim(simCounts)  # nTime x nUnit x nsim
[1] 312   1   1
> ## Don't show: 
> stopifnot(observed(simData) == c(simCounts))
> ## End(Don't show)
> # plot the first year of simulated counts (+ initial + observed)
> plot(simCounts[1:52,,], type = "time", xaxis.labelFormat = NULL)
> # see help(plot.hhh4sims) for other plots, mainly useful for nsim > 1
> 
> # simulate from a Poisson instead of a NegBin model
> # keeping all other parameters fixed at their original estimates
> coefs <- replace(coef(fit), "overdisp", 0)
> simData2 <- simulate(fit, seed=123, coefs = coefs)
> plot(simData2, main = "simulated data: Poisson model", xaxis.labelFormat = NULL)
> 
> # simulate from a model with higher autoregressive parameter
> coefs <- replace(coef(fit), "ar.1", log(0.9))
> simData3 <- simulate(fit, seed=321, coefs = coefs)
> plot(simData3, main = "simulated data: lambda = 0.5", xaxis.labelFormat = NULL)
> 
> 
> ## more sophisticated: simulate beyond initially observed time range
> 
> # extend data range by one year (non-observed domain), filling with NA values
> nextend <- 52
> timeslots <- c("observed", "state", "alarm", "upperbound", "populationFrac")
> addrows <- function (mat, n) mat[c(seq_len(nrow(mat)), rep(NA, n)),,drop=FALSE]
> extended <- Map(function (x) addrows(slot(meningo, x), n = nextend), x = timeslots)
> # create new sts object with extended matrices
> meningo2 <- do.call("sts", c(list(start = meningo@start, frequency = meningo@freq,
+                                   map = meningo@map), extended))
> 
> # fit to the observed time range only, via the 'subset' argument
> fit2 <- hhh4(meningo2, control = list(
+               ar = list(f = ~ 1),
+               end = list(f = addSeason2formula(~1, period = 52)),
+               family = "NegBin1",
+               subset = 2:(nrow(meningo2) - nextend)))
> # the result is the same as before
> stopifnot(all.equal(fit, fit2, ignore = c("stsObj", "control")))
> ## Don't show: 
> # one-week-ahead prediction only "works" for the first non-observed time point
> # because the autoregressive component relies on non-missing past counts
> oneStepAhead(fit2, tp = rep(nrow(meningo2)-nextend, 2), type = "final", verbose = FALSE)
$pred
    meningococcus
313      11.45203

$observed
    meningococcus
313            NA

$psi
    -log(overdisp)
312       3.012411

$allConverged
[1] TRUE

attr(,"class")
[1] "oneStepAhead"
> # however, methods won't work as observed is NA
> ## End(Don't show)
> # long-term probabilistic forecast via simulation for non-observed time points
> meningoSim <- simulate(fit2, nsim = 100, seed = 1,
+                        subset = seq(nrow(meningo)+1, nrow(meningo2)),
+                        y.start = tail(observed(meningo), 1))
> apply(meningoSim, 1:2, function (ysim) quantile(ysim, c(0.1, 0.5, 0.9)))
Error in x@observed[i, j, drop = FALSE] : subscript out of bounds
Calls: apply ... subset_hhh4sims_attributes -> suppressMessages -> withCallingHandlers -> [ -> [
Execution halted
Examples with CPU (user + system) or elapsed time > 5s
               user system elapsed
epidataCS_plot 4.12  0.004   5.564