Methods to compute linear h-step ahead prediction coefficients based on localised and iterated Yule-Walker estimates and empirical mean squared 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. (2017), Preprint arXiv:1611.04460 .

Documentation

Manual: forecastSNSTS.pdf
Vignette: None available.

Maintainer: Tobias Kley <t.kley at lse.ac.uk>

Author(s): Tobias Kley*, Philip Preuss*, Piotr Fryzlewicz*

Install package and any missing dependencies by running this line in your R console:

install.packages("forecastSNSTS")

Depends R (>= 3.2.3)
Imports Rcpp
Suggests testthat
Enhances
Linking to Rcpp
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Package forecastSNSTS
Materials
URL http://github.com/tobiaskley/forecastSNSTS
Task Views
Version 1.1-1
Published 2017-01-20
License GPL (>= 2)
BugReports http://github.com/tobiaskley/forecastSNSTS/issues
SystemRequirements
NeedsCompilation yes
Citation
CRAN checks forecastSNSTS check results
Package source forecastSNSTS_1.1-1.tar.gz