The R package Dejavu
provides efficient algorithms for forecasting with Similarity of a bunch of time series.
You can install Dejavu
package from GitHub Repository with:
devtools::install_github("kdwang1808/Dejavu")
require("Dejavu")
-
Using Reference data from M3 Competition (Download the repository to local first)
library(dtw) library(robustbase) library(forecast) fc_Simi <- Similarity(AirPassengers, fh = 20, LoadData = TRUE, path = NULL) fcs_result <- ts(fc_Simi$fcs, start = 1961, frequency = 12) PIL_result <- ts(fc_Simi$PIL, start = 1961, frequency = 12) PIU_result <- ts(fc_Simi$PIU, start = 1961, frequency = 12) autoplot(AirPassengers)+autolayer(fcs_result)+autolayer(PIL_result)+autolayer(PIU_result)
-
Using "Mydata" as Reference
fc_Simi <- Similarity(AirPassengers, fh = 20, LoadData = FALSE, path = "Mydata")
-
Yanfei Kang, Evangelos Spiliotis, Fotios Petropoulos, Nikolaos Athiniotis, Feng Li, Vassilios Assimakopoulos (2019). D´ej`a vu: forecasting with similarity.
This package is free and open source software, licensed under GPL-3.