odpc: One-Sided Dynamic Principal Components

Functions to compute the one-sided dynamic principal components ('odpc') introduced in Peña, Smucler and Yohai (2019) <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 <daniel.pena@uc3m.es>, Ezequiel Smucler <ezequiels.90@gmail.com>, Victor Yohai <vyohai@dm.uba.ar>
MaintainerEzequiel Smucler <ezequiels.90@gmail.com>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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odpc documentation built on Nov. 16, 2020, 9:15 a.m.