tobiaskley/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 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. (2017), Preprint <http://personal.lse.ac.uk/kley/forecastSNSTS.pdf>.

Getting started

Package details

Maintainer
LicenseGPL (>= 2)
Version1.2-0.9000
URL http://github.com/tobiaskley/forecastSNSTS
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("tobiaskley/forecastSNSTS")
tobiaskley/forecastSNSTS documentation built on May 31, 2019, 4:43 p.m.