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 <>.

Install the latest version of this package by entering the following in R:
AuthorTobias Kley [aut, cre], Philip Preuss [aut], Piotr Fryzlewicz [aut]
Date of publication2017-01-20 10:48:10
MaintainerTobias Kley <>
LicenseGPL (>= 2)

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