Package: forecastSNSTS
Title: Forecasting for Stationary and Non-Stationary Time Series
Version: 1.3-0
Authors@R: c(person("Tobias", "Kley", email = "tobias.kley@bristol.ac.uk", role = c("aut", "cre")),
             person("Philip", "Preuss", email = "philip.preuss@rub.de", role = c("aut")),
             person("Piotr", "Fryzlewicz", email = "p.fryzlewicz@lse.ac.uk", role = c("aut")))
Description: 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>.
Depends: R (>= 3.2.3)
License: GPL (>= 2)
URL: http://github.com/tobiaskley/forecastSNSTS
BugReports: http://github.com/tobiaskley/forecastSNSTS/issues
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp
Imports: Rcpp
Collate: 'RcppExports.R' 'acfARp.R' 'f.R' 'forecastSNSTS-package.R'
        'measure-of-accuracy.R' 'models.R'
RoxygenNote: 6.1.1
Suggests: testthat
NeedsCompilation: yes
Packaged: 2019-09-02 13:51:50 UTC; tk18582
Author: Tobias Kley [aut, cre],
  Philip Preuss [aut],
  Piotr Fryzlewicz [aut]
Maintainer: Tobias Kley <tobias.kley@bristol.ac.uk>
Repository: CRAN
Date/Publication: 2019-09-02 15:20:05 UTC
Built: R 4.6.0; aarch64-apple-darwin23; 2026-04-25 18:59:55 UTC; unix
Archs: forecastSNSTS.so.dSYM
