README.md

In jonlachmann/sparsecoint: Forecasting using sparse cointegration

sparsecoint

This package implements the algorithm described in the paper "Forecasting using sparse cointegration" by Ines Wilms and Christophe Croux, available at https://doi.org/10.1016/j.ijforecast.2016.04.005.

The code is based on the code that was made available with the paper, but should be easier to use by a novice user.

To install the package run the following:

library(devtools)
install_github("jonlachmann/glassor")
install_github("jonlachmann/sparsecoint")

To build a model the function sparsecoint is used, an example is given below, where a forecast is also made and plotted:

library(sparsecoint)
model <- sparsecoint(data, p=12, intercept=TRUE)
forecast <- predict(model, h=12, samples=500)
plot(forecast)

jonlachmann/sparsecoint documentation built on April 14, 2022, 10:49 a.m.