knitr::opts_chunk$set(message = FALSE, warning = FALSE, error = FALSE, fig.align = "center", dev.args = list(pointsize = 10)) options(knitr.duplicate.label = "allow")
options(digits = 4) # for more compact numerical outputs library("surveillance") library("hhh4contacts")
In this vignette, we assess long-term forecasts of the "hhh4" models from
vignette("BNV")
using:
library("hhh4addon")
This package is developed by Johannes Bracher and available from
r packageDescription("hhh4addon", fields = "URL")
.
We rerun the code from the vignette("BNV")
to make the models available:
rmarkdown::render(system.file("doc", "BNV.Rmd", package = "HIDDA.forecasting"), run_pandoc = FALSE, envir = BNV <- new.env(), quiet = TRUE)
(MODELS <- names(BNV$fits)) NMODELS <- length(MODELS)
statmoms <- lapply(BNV$fits, stationary_moments, start = 27) ## illustration for age group 00-04 .group <- 1 par(mfrow = n2mfrow(NMODELS), mar = c(5,5,2,1)) invisible(mapply(fanplot_stationary, statmoms, main = names(statmoms), MoreArgs = list(unit = .group, xlab = "Time within season", mean_col = "white", mean_lty = 1)))
predmoms <- lapply(BNV$fits, predictive_moments, t_condition = 208, lgt = 52, return_Sigma = TRUE) ## illustration for age group 00-04 .group <- 1 par(mfrow = n2mfrow(NMODELS), mar = c(5,5,2,1), las = 1) invisible(mapply(fanplot_prediction, predmoms, main = names(predmoms), MoreArgs = list(unit = .group, xlab = "Time", ylim = c(0, 55), mean_col = "white", mean_lty = 1, l.col = NA, pt.col = 1, pt.cex = 0.4)))
Scaled Dawid-Sebastiani scores of these multivariate forecast distributions:
sapply(predmoms, ds_score_hhh4, detailed = TRUE)
aggr <- matrix(rep(diag(BNV$NGROUPS), 52), nrow = BNV$NGROUPS, dimnames = list(BNV$GROUPS, NULL)) predmoms_aggr <- lapply(predmoms, aggregate_moments, aggregation_matrix = aggr) par(mfrow = n2mfrow(NMODELS), mar = c(5,5,2,1), las = 2, cex.axis = 0.8) invisible(mapply(plot_moments_by_unit, predmoms_aggr, main = names(predmoms_aggr), MoreArgs = list(xlab = "Age group", ylim = c(0, 3000), pt.col = 2, pt.cex = 0.6)))
Scaled Dawid-Sebastiani scores of these multivariate forecast distributions:
sapply(predmoms_aggr, ds_score_hhh4, detailed = TRUE)
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