Methods to compute linear h-step ahead prediction coefficients based on localised and iterated Yule-Walker estimates and empirical mean squared and absolute prediction errors for the resulting predictors. Also, functions to compute autocovariances for AR(p) processes, to simulate tvARMA(p,q) time series, and to verify an assumption from Kley et al. (2019), Electronic of Statistics, forthcoming. Preprint <arXiv:1611.04460>.
Version: | 1.3-0 |
Depends: | R (≥ 3.2.3) |
Imports: | Rcpp |
LinkingTo: | Rcpp |
Suggests: | testthat |
Published: | 2019-09-02 |
Author: | Tobias Kley [aut, cre], Philip Preuss [aut], Piotr Fryzlewicz [aut] |
Maintainer: | Tobias Kley <tobias.kley at bristol.ac.uk> |
BugReports: | http://github.com/tobiaskley/forecastSNSTS/issues |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
URL: | http://github.com/tobiaskley/forecastSNSTS |
NeedsCompilation: | yes |
Materials: | README NEWS |
CRAN checks: | forecastSNSTS results |
Reference manual: | forecastSNSTS.pdf |
Package source: | forecastSNSTS_1.3-0.tar.gz |
Windows binaries: | r-devel: forecastSNSTS_1.3-0.zip, r-release: forecastSNSTS_1.3-0.zip, r-oldrel: forecastSNSTS_1.3-0.zip |
macOS binaries: | r-release (arm64): forecastSNSTS_1.3-0.tgz, r-oldrel (arm64): forecastSNSTS_1.3-0.tgz, r-release (x86_64): forecastSNSTS_1.3-0.tgz, r-oldrel (x86_64): forecastSNSTS_1.3-0.tgz |
Old sources: | forecastSNSTS archive |
Please use the canonical form https://CRAN.R-project.org/package=forecastSNSTS to link to this page.