The R package hts presents functions to create, plot and forecast hierarchical and grouped time series. In forecasting hierarchical and grouped time series, the base methods implemented include ETS, ARIMA and the naive (random walk) models. Forecasts for grouped time series are calibrated using bottom-up and optimal combination methods. Forecasts for hierarchical time series are distributed in the hierarchy using bottom-up, top-down, middle-out and optimal combination methods. Three top-down methods are available: the two Gross-Sohl methods and the forecast-proportion approach of Hyndman, Ahmed, and Athanasopoulos (2011).
You can install the stable version on R CRAN.
install.packages('hts', dependencies = TRUE)You can also install the development version from Github
# install.packages("devtools")
library(devtools)
install_github("hts", "robjhyndman") # library(hts)
demo(htseg1) # hts example 1
demo(htseg2) # hts example 2
demo(infantgts) # gtsThis package is free and open source software, licensed under GPL (>= 2).