forecastSNSTS: Forecasting for Stationary and Non-Stationary Time Series

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 <http://arxiv.org/abs/1611.04460>.

AuthorTobias Kley [aut, cre], Philip Preuss [aut], Piotr Fryzlewicz [aut]
Date of publication2017-01-20 10:48:10
MaintainerTobias Kley <t.kley@lse.ac.uk>
LicenseGPL (>= 2)
Version1.1-1
http://github.com/tobiaskley/forecastSNSTS

View on CRAN

Files

forecastSNSTS
forecastSNSTS/inst
forecastSNSTS/inst/examples
forecastSNSTS/inst/examples/mspe.R
forecastSNSTS/inst/examples/computeMSPE.R
forecastSNSTS/inst/examples/tvARMA.R
forecastSNSTS/tests
forecastSNSTS/tests/testthat.R
forecastSNSTS/tests/testthat
forecastSNSTS/tests/testthat/test-tvARMA.R
forecastSNSTS/tests/testthat/test-MSPE.R
forecastSNSTS/tests/testthat/test-computeMSPE.R
forecastSNSTS/tests/testthat/test-f.R
forecastSNSTS/tests/testthat/test-acfARp.R
forecastSNSTS/tests/testthat/test-coefficients.R
forecastSNSTS/src
forecastSNSTS/src/computeMSPE.cpp
forecastSNSTS/src/predCoef.cpp
forecastSNSTS/src/tvARMA.cpp
forecastSNSTS/src/RcppExports.cpp
forecastSNSTS/NAMESPACE
forecastSNSTS/demo
forecastSNSTS/demo/tvARMA11.R
forecastSNSTS/demo/00Index
forecastSNSTS/NEWS
forecastSNSTS/R
forecastSNSTS/R/models.R forecastSNSTS/R/acfARp.R forecastSNSTS/R/forecastSNSTS-package.R forecastSNSTS/R/mspe.R forecastSNSTS/R/RcppExports.R forecastSNSTS/R/f.R
forecastSNSTS/MD5
forecastSNSTS/DESCRIPTION
forecastSNSTS/man
forecastSNSTS/man/MSPE.Rd forecastSNSTS/man/forecastSNSTS-package.Rd forecastSNSTS/man/ts-models-tvARMA.Rd forecastSNSTS/man/predCoef.Rd forecastSNSTS/man/plot.MSPE.Rd forecastSNSTS/man/acfARp.Rd forecastSNSTS/man/f.Rd

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