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.
|Author||Tobias Kley [aut, cre], Philip Preuss [aut], Piotr Fryzlewicz [aut]|
|Date of publication||2016-11-17 18:07:28|
|Maintainer||Tobias Kley <firstname.lastname@example.org>|
|License||GPL (>= 2)|
acfARp: Compute autocovariances of an AR(p) process
f: Compute f(delta) for a tvAR(p) process
forecastSNSTS-package: Forecasting of Stationary and Non-Stationary Time Series
MSPE: Mean squared h-step ahead prediction errors
plot.MSPE: Plot a 'MSPE' object
predCoef: h-step Prediction coefficients
ts-models-tvARMA: Simulation of an tvARMA(p) time series.