In this package we implement functions for forecast univariate time series using the several Theta Models (Fiorucci et al, 2015 and 2016) and
the Standard Theta Method of Assimakopoulos & Nikolopoulos (2000).
Moreover, it is including a function for compute the main errors metrics used in time series forecasting and a function for compute the
Generalised Rolling Origin Evaluation, which contain as particular cases the Rolling Origin Evaluation and the Fixed Origin Evaluation of Tashman (2000).
Details
Package:
forecTheta
Type:
Package
Version:
2.2
Date:
2016-05-25
License:
GPL (>=2.0)
dotm(y, h)
stheta(y, h)
errorMetric(obs, forec, type = "sAPE", statistic = "M")
groe(y, forecFunction = ses, g = "sAPE", n1 = length(y)-10)
Author(s)
Jose Augusto Fiorucci, Francisco Louzada and Bao Yiqi
Maintainer: Jose Augusto Fiorucci <jafiorucci@gmail.com>
Fiorucci J.A., Pellegrini T.R., Louzada F., Petropoulos F. (2015). The Optimised Theta Method. Free available at http://arxiv.org/abs/1503.03529.
Assimakopoulos, V. and Nikolopoulos k. (2000). The theta model: a decomposition approach to forecasting. International Journal of Forecasting 16, 4, 521–530.
Tashman, L.J. (2000). Out-of-sample tests of forecasting accuracy: an analysis and review. International Journal of Forecasting 16 (4), 437–450.