print.rlgtfit

summary.rlgt

Print out some characteristics of an <code>rlgtfit</code> model.

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.

Christoph Bergmeir

Rlgt

Bayesian Exponential Smoothing Models with Trend Modifications

Slawek Smyl

Erwin Wibowo

To Wang Ng

Xueying Long

Alexander Dokumentov

Daniel Schmidt

Trustees of Columbia University 

print.rlgtfit function

<dl><dt>x</dt>
<dd>an rlgtfit object</dd>
<dt>...</dt>
<dd>additional function parameters (currently not used)</dd></dl>

Arguments

Generic print function for rlgtfit models — print.rlgtfit

<dl>

<dt>x</dt>
<dd>an rlgtfit object</dd>


<dt>...</dt>
<dd>additional function parameters (currently not used)</dd>

</dl>

Generic print function for rlgtfit models

print.rlgtfit: Generic print function for rlgtfit models

Description

Usage

Arguments