evaluation

Specify the way in which the estimation of forecast accuracy is done

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

evaluation function

<dl><dt>type</dt>
<dd>A string. Possible values are <code>"normal"</code> (the default) and
<code>"minimum"</code>. See the vignette for an explanation of both ways of evaluating
forecast accuracy.</dd>
<dt>size</dt>
<dd>An integer. It is the size of the test set (how many of the last
observations of the time series are used as test set). It can only be used
when the type parameter is <code>"normal"</code>.</dd>
<dt>prop</dt>
<dd>A numeric value in the range (0, 1). It is the proportion of the
time series used as test set. It can only be used when the type parameter
is <code>"normal"</code>.</dd></dl>

Arguments

Specify the way in which the estimation of forecast accuracy is done — evaluation

<dl>

<dt>type</dt>
<dd>A string. Possible values are <code>"normal"</code> (the default) and
<code>"minimum"</code>. See the vignette for an explanation of both ways of evaluating
forecast accuracy.</dd>


<dt>size</dt>
<dd>An integer. It is the size of the test set (how many of the last
observations of the time series are used as test set). It can only be used
when the type parameter is <code>"normal"</code>.</dd>


<dt>prop</dt>
<dd>A numeric value in the range (0, 1). It is the proportion of the
time series used as test set. It can only be used when the type parameter
is <code>"normal"</code>.</dd>

</dl>

evaluation: Specify the way in which the estimation of forecast accuracy is done

Description

Usage

Value

Arguments

Examples