ahead is a package for univariate and
multivariate time series forecasting, with uncertainty
quantification (R and Python).
The model used in this demo is stats::ridge2f.
Please remember that in real life, this model’s hyperparameters will have to be tuned.
Install ahead
Here’s how to install the R version of the package:
-
1st method: from R-universe
In R console:
options(repos = c( techtonique = 'https://techtonique.r-universe.dev', CRAN = 'https://cloud.r-project.org')) install.packages("ahead") -
2nd method: from Github
In R console:
devtools::install_github("Techtonique/ahead")Or
remotes::install_github("Techtonique/ahead")
And here are the packages that will be used in this vignette:
Forecasting and plot predictions
obj <- ahead::ridge2f(fpp::insurance, h = 7, type_pi = "blockbootstrap", B = 10,
block_length = 5)
#>
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plot(obj, selected_series = "Quotes", type = "sims",
main = "Predictive simulations \n for Quotes")
plot(obj, selected_series = "Quotes", type = "dist",
main = "Predictive simulation \n for Quotes")
plot(obj, selected_series = "TV.advert", type = "sims",
main = "Predictive simulation \n for TV.advert")
plot(obj, selected_series = "TV.advert", type = "dist",
main = "Predictive simulation \n for TV.advert")