Package 'Rlgt'
| Title: |
Bayesian Exponential Smoothing Models with Trend Modifications |
| Description: |
An implementation of a number of Global Trend models for
time series forecasting that are Bayesian generalizations and
extensions of some Exponential Smoothing models. The main
differences/additions include 1) nonlinear global trend, 2)
Student-t error distribution, and 3) a function for the error
size, so heteroscedasticity. The methods are particularly
useful for short time series. When tested on the well-known M3
dataset, they are able to outperform all classical time series
algorithms. The models are fitted with MCMC using the 'rstan'
package. |
| Authors: |
Slawek Smyl [aut],
Christoph Bergmeir [aut, cre],
Erwin Wibowo [aut],
To Wang Ng [aut],
Xueying Long [aut],
Alexander Dokumentov [aut],
Daniel Schmidt [aut],
Trustees of Columbia University [cph] (tools/make_cpp.R,
R/stanmodels.R) |
| Maintainer: |
Christoph Bergmeir <[email protected]> |
| License: |
GPL-3 |
| Version: |
0.2-2 |
| Built: |
2024-11-22 02:22:24 UTC |
| Source: |
https://github.com/cbergmeir/rlgt |
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