print.scam

The default print method for a <code>scam</code> object. The code is a clone of <code>print.gam</code>
of the <code>mgcv</code> package with a slight simplification since only two methods of smoothing parameter 
selection (by GCV or UBRE) was implemented for <code>scam</code>.

models

regression

smooth

Generalized additive models under shape
constraints on the component functions of the linear predictor.
Models can include multiple shape-constrained (univariate
and bivariate) and unconstrained terms. Routines of the
package 'mgcv' are used to set up the model matrix, print,
and plot the results. Multiple smoothing parameter
estimation by the Generalized Cross Validation or similar.
See Pya and Wood (2015) <doi:10.1007/s11222-013-9448-7>
for an overview. A broad selection of shape-constrained
smoothers, linear functionals of smooths with shape constraints,
and Gaussian models with AR1 residuals.

Natalya Pya

scam

Shape Constrained Additive Models

print.scam function

<dl><dt>x</dt>
<dd>fitted model objects of class <code>scam</code> as produced by <code>scam()</code>.</dd>
<dt>...</dt>
<dd>other arguments.</dd>
</dl>

Arguments

Natalya Pya &lt;nat.pya@gmail.com&gt;

Author

Print a SCAM object — print.scam

<dl>

<dt>x</dt>
<dd>fitted model objects of class <code>scam</code> as produced by <code>scam()</code>.</dd>


<dt>...</dt>
<dd>other arguments.</dd>


</dl>

Natalya Pya &lt;nat.pya@gmail.com&gt;

print.scam: Print a SCAM object

Description

Usage

Arguments

Author

Details

References

See Also