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The goal of flap is to provide the Forecast Linear Augmented Projection method that can reduce forecast variance by adjusting the forecasts of multivariate time series to be consistent with the forecasts of linear combinations (components) of the series by projecting all forecasts onto the space where the linear constraints are satisfied.
You can install the stable version from CRAN.
You can install the development version from Github
This is a basic workflow to flap:
## The following pacakges are required to run this example
# install.packages("tidyr")
# install.packages("ggplot2")
# install.packages("forecast")
# install.packages("fpp2")
library(flap)
library(tidyr)
library(ggplot2)
# Obtain the forecast and the residual of the original series
mdl <- apply(fpp2::visnights, 2, forecast::ets)
#> Registered S3 method overwritten by 'quantmod':
#> method from
#> as.zoo.data.frame zoo
fc <- vapply(mdl, function(mdl) forecast::forecast(mdl, h=12)$mean,
FUN.VALUE = numeric(12))
res <- vapply(mdl, residuals,
FUN.VALUE = numeric(nrow(fpp2::visnights)))
# Obtain components and their forecasts and residuals
pca <- stats::prcomp(fpp2::visnights, center = FALSE, scale. = FALSE)
mdl_comp <- apply(pca$x, 2, forecast::ets)
fc_comp <- vapply(mdl_comp, function(mdl) forecast::forecast(mdl, h=12)$mean,
FUN.VALUE = numeric(12))
res_comp <- vapply(mdl_comp, residuals,
FUN.VALUE = numeric(nrow(pca$x)))
Phi <- t(pca$rotation)
# flap!
proj_fc <- flap(fc, fc_comp, Phi, res, res_comp)
proj_fc
#> Forecast Linear Augmented Projection
#> A named list of numeric matrices of projected forecasts
#> ------------
#> Num. of Series: m = 20
#> Num. of Components: p = 1-20
#> Num. of Forecast Horizons: 12
#> ------------
#> List of 20
#> $ 1 : num [1:12, 1:20] 7.8 7.91 ...
#> $ 2 : num [1:12, 1:20] 7.64 7.76 ...
#> $ 3 : num [1:12, 1:20] 7.64 7.78 ...
#> $ 4 : num [1:12, 1:20] 7.39 7.48 ...
#> $ 5 : num [1:12, 1:20] 7.39 7.49 ...
#> [list output truncated]
# Plot
if(interactive()) {
proj_fc %>%
as.data.frame() %>%
pivot_longer(!c(h, p)) %>%
ggplot(aes(x = h, y = value, colour = p, group = p)) +
geom_line() +
facet_wrap("name", scales = "free_y")
}These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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