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.

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Description file content

Package
odpc
Type
Package
Title
One-Sided Dynamic Principal Components
Version
2.0.0
Date
2018-09-11
Author
Daniel Peña , Ezequiel Smucler , Victor Yohai
Maintainer
Ezequiel Smucler
Description
Functions to compute the one-sided dynamic principal components ('odpc') introduced in Smucler, Peña and Yohai (2018) . '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.
License
GPL (>= 2)
Biarch
true
Imports
methods, Rcpp (>= 0.12.7), forecast, parallel, doParallel, foreach
LinkingTo
Rcpp, RcppArmadillo (>= 0.7.500.0.0)
Suggests
testthat
Depends
R (>= 3.3.0)
NeedsCompilation
yes
Encoding
UTF-8
RoxygenNote
6.0.1
Packaged
2018-09-11 22:34:18 UTC; ezequiel
Repository
CRAN
Date/Publication
2018-09-12 04:20:03 UTC

install.packages('odpc')

2.0.0

10 days ago

Ezequiel Smucler

GPL (>= 2)

Depends on

R (>= 3.3.0)

Imports

methods, Rcpp (>= 0.12.7), forecast, parallel, doParallel, foreach

Suggests

testthat

Discussions