forecastSNSTS (1.1-0)

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 a paper by the authors.

Maintainer: Tobias Kley
Author(s): Tobias Kley [aut, cre], Philip Preuss [aut], Piotr Fryzlewicz [aut]

License: GPL (>= 2)

Uses: Rcpp, testthat

Released over 2 years ago.