Function constructs a plot for two categorical variables based on table function

tableplot

Implements functions and instruments for regression model building and its
application to forecasting. The main scope of the package is in variables selection
and models specification for cases of time series data. This includes promotional
modelling, selection between different dynamic regressions with non-standard
distributions of errors, selection based on cross validation, solutions to the fat
regression model problem and more. Models developed in the package are tailored
specifically for forecasting purposes. So as a results there are several methods
that allow producing forecasts from these models and visualising them.

Ivan Svetunkov

greybox

Toolbox for Model Building and Forecasting

Yves R. Sagaert

tableplot function

Construct a plot for categorical variable — tableplot

<dl>

<dt>x</dt>
<dd>First categorical variable. Can be either vector, factor, matrix or a data
frame. If <code>y</code> is NULL and x is either matrix of a data frame, then the first two
variables of the data will be plotted against each other.</dd>


<dt>y</dt>
<dd>Second categorical variable. If not provided, then only <code>x</code> will be
plotted.</dd>


<dt>labels</dt>
<dd>Whether to print table labels inside the plot or not.</dd>


<dt>legend</dt>
<dd>If <code>TRUE</code>, then the legend for the tableplot is drawn. The plot is
then produced on a separate canvas (new <code><a href='https://rdrr.io/r/graphics/par.html'>par()</a></code>).</dd>


<dt>points</dt>
<dd>Whether to plot points in the areas. They help in understanding how
many values lie in specific categories.</dd>


<dt>...</dt>
<dd>Other parameters passed to the plot function.</dd>

</dl>

Arguments

Ivan Svetunkov, <a href='mailto:ivan@svetunkov.com'>ivan@svetunkov.com</a>

tableplot: Construct a plot for categorical variable

Description

Usage

Arguments

Value

Details

See Also

Examples