build_examples

Build the training examples for a regressive model to forecast a time series
using lagged values of the series as autoregressive features.

An engine for univariate time series forecasting using
different regression models in an autoregressive way. The engine
provides an uniform interface for applying the different models.
Furthermore, it is extensible so that users can easily apply their
own regression models to univariate time series forecasting and
benefit from all the features of the engine, such as preprocessings
or estimation of forecast accuracy.

Francisco Martinez

utsf

Univariate Time Series Forecasting

Maria Pilar Frias-Bustamante

build_examples function

<dl><dt>timeS</dt>
<dd>The time series.</dd>
<dt>lags</dt>
<dd>An integer vector with the lags used as feature vector in
decreasing order.</dd></dl>

Arguments

Build the training examples — build_examples

<dl>

<dt>timeS</dt>
<dd>The time series.</dd>


<dt>lags</dt>
<dd>An integer vector with the lags used as feature vector in
decreasing order.</dd>

</dl>

build_examples: Build the training examples

Description

Usage

Value

Arguments

Examples