formula.scam

Description of <code>scam</code> formula (see <code>gam</code> of the <code>mgcv</code> package for Details), and how to extract it from a fitted <code>scam</code> object.
The function is a clone of <code><a href="/link/formula.gam?package=scam&version=1.2-17" data-mini-rdoc="scam::formula.gam">formula.gam</a></code> of the <code>mgcv</code> package.

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

formula.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>un-used in this case</dd>
 
</dl>

Arguments

Description of <code>scam</code> formula (see <code>gam</code> of the <code>mgcv</code> package for Details), and how to extract it from a fitted <code>scam</code> object.
The function is a clone of <code><a href='https://rdrr.io/pkg/mgcv/man/formula.gam.html'>formula.gam</a></code> of the <code>mgcv</code> package.

SCAM formula — formula.scam

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

<dt>...</dt>
<dd>un-used in this case</dd>
 
</dl>

formula.scam: SCAM formula

Description

Usage

Value

Arguments

Details

See Also