jdestefani/ExtendedDFML: Extended Dynamic Factor Machine Learner

The package implement a modular version of the DFML Algorithm (https://doi.org/10.1007/s41060-018-0150-x), supporting multiple forecasting techniques and multiple dimensionaliity reduction techniques. The forecasting techniques supported are the M4 benchmarks (via a custom package), state-of-the-art multistep ahead techniques (k-NN, RF both in a direct and recursive fashion and MIMO, via gbcode), and gradient boosting techniques (XGBoost and LightGBM, via the corresponding packages).

Getting started

Package details

Maintainer
LicenseGPL-3 + file LICENSE
Version0.1.0.0
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("jdestefani/ExtendedDFML")
jdestefani/ExtendedDFML documentation built on Dec. 20, 2021, 10:04 p.m.