plot,GeDSgam-method

plot.GeDSgam

plot,GeDSgam,ANY-method

Plots on the linear predictor scale the component functions of a GeDSgam
object fitted using <code>NGeDSgam</code>.

Spline Regression, Generalized Additive Models, and Component-wise Gradient
Boosting, utilizing Geometrically Designed (GeD) Splines. GeDS regression is a
non-parametric method inspired by geometric principles, for fitting spline regression
models with variable knots in one or two independent variables. It efficiently estimates
the number of knots and their positions, as well as the spline order, assuming the
response variable follows a distribution from the exponential family. GeDS models
integrate the broader category of Generalized (Non-)Linear Models, offering a flexible
approach to modeling complex relationships. A description of the method can be found in
Kaishev et al. (2016) <doi:10.1007/s00180-015-0621-7> and Dimitrova et al. (2023)
<doi:10.1016/j.amc.2022.127493>. Further extending its capabilities, GeDS's implementation
includes Generalized Additive Models (GAM) and Functional Gradient Boosting (FGB),
enabling versatile multivariate predictor modeling, as discussed in the forthcoming work of
Dimitrova et al. (2024).

Emilio Guillen

GeDS

Geometrically Designed Spline Regression

Andrea Lattuada

plot,GeDSgam-method function

<dl><dt>x</dt>
<dd>a <code>GeDSgam-class</code> object from which the GeDSgam fit(s) should
be extracted.</dd>
<dt>base_learners</dt>
<dd>either NULL or a vector of character string specifying
the base-learners of the model for which predictions should be plotted. Note
that single base-learner predictions are provided on the linear predictor scale.</dd>
<dt>f</dt>
<dd>(optional) specifies the underlying component function or generating
process to which the model was fit. This parameter is useful if the user wishes
to plot the specified function/process alongside the model fit and the data.</dd>
<dt>n</dt>
<dd>integer value (2, 3 or 4) specifying the order (\(=\) degree
\(+ 1\)) of the GAM-GeDS fit.</dd>
<dt>...</dt>
<dd>further arguments to be passed to the
<code><a href="/link/plot.default?package=GeDS&version=0.2.5" data-mini-rdoc="GeDS::plot.default">plot.default</a></code> function.</dd></dl>

Arguments

Plot method for GeDSgam objects. — plot,GeDSgam-method

<dl>

<dt>x</dt>
<dd>a <code>GeDSgam-class</code> object from which the GeDSgam fit(s) should
be extracted.</dd>


<dt>base_learners</dt>
<dd>either NULL or a vector of character string specifying
the base-learners of the model for which predictions should be plotted. Note
that single base-learner predictions are provided on the linear predictor scale.</dd>


<dt>f</dt>
<dd>(optional) specifies the underlying component function or generating
process to which the model was fit. This parameter is useful if the user wishes
to plot the specified function/process alongside the model fit and the data.</dd>


<dt>n</dt>
<dd>integer value (2, 3 or 4) specifying the order (\(=\) degree
\(+ 1\)) of the GAM-GeDS fit.</dd>


<dt>...</dt>
<dd>further arguments to be passed to the
<code><a href='https://rdrr.io/r/graphics/plot.default.html'>plot.default</a></code> function.</dd>

</dl>

plot,GeDSgam-method: Plot method for GeDSgam objects.

Description

Usage

Arguments