The R package M4comp2018 contains the 100000 time series from the M4-competition. It also includes the true future values (the test part) and the submitted forecasts of the top25 participants.
install.packages("https://github.com/carlanetto/M4comp2018/releases/download/0.2.0/M4comp2018_0.2.0.tar.gz",
repos=NULL)The M4 object is a list with the series. Each element of this list is also a list with some components, like the series, the future values, type and domain and the submitted forecasts.
## check the components of the least
library(M4comp2018)
data(M4)
names(M4[[1]])
#> [1] "st" "x" "n" "type" "h" "period" "xx"
#> [8] "pt_ff" "up_ff" "low_ff"
#extract yearly series
yearly_M4 <- Filter(function(l) l$period == "Yearly", M4)#plot one of the series, in red the future data
#in black, the hitorical data
plot(ts(c(M4[[40773]]$x, M4[[40773]]$xx),
start=start(M4[[40773]]$x), frequency = frequency(M4[[40773]]$x)),
col="red", type="l", ylab="")
lines(M4[[40773]]$x, col="black")
#read the help file for documentation
?M4comp2018You can check the point forecasts subissions in the $pt_ff of each element of the list. Info about the submissions is in the submission_info dataframe, the order of $pt_ff is the OWA ranking. Upper and Lower bound prediction intervals are found in $up_ff and $low_ff respectively.
?submission_infoM4[[1]]$pt_ff[1:3, ]
#> [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,] 7243.994 7288.752 7333.678 7376.056 7423.142 7472.488
#> [2,] 7291.322 7333.897 7376.682 7419.546 7462.400 7505.190
#> [3,] 7172.993 7075.970 6997.268 6932.078 6876.902 6829.184
data(submission_info)
#check some info about top 3 sumbissions
submission_info[1:3,]
#> ID Type Author(s)
#> 1 118 Hybrid Smyl
#> 2 245 Combination Montero-Manso, et al.
#> 3 237 Combination Pawlikowski, et al.
#> Affiliation Rank(OWA)
#> 1 Uber Technologies 1
#> 2 University of A Coruna & Monash University 2
#> 3 ProLogistica Soft 3This package is free and open source software, licensed under GPL-3