esmucler/odpc: One-Sided Dynamic Principal Components

Functions to compute the one-sided dynamic principal components ('odpc') introduced in Smucler, Peña and Yohai (2018) <DOI:10.1080/01621459.2018.1520117>. 'odpc' is a novel dimension reduction technique for multivariate time series, that is useful for forecasting. These dynamic principal components are defined as the linear combinations of the present and past values of the series that minimize the reconstruction mean squared error.

Getting started

Package details

AuthorDaniel Peña <[email protected]>, Ezequiel Smucler <[email protected]>, Victor Yohai <[email protected]>
MaintainerEzequiel Smucler <[email protected]>
LicenseGPL (>= 2)
Version2.0.0
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("esmucler/odpc")
esmucler/odpc documentation built on Sept. 24, 2018, 6:15 p.m.