logLik.scam

AIC.scam

Function to extract the log-likelihood for a fitted <code>scam</code>
model (fitted by penalized likelihood maximization). 
Used by <code>AIC</code>.
The function is a clone of <code><a href="/link/logLik.gam?package=scam&version=1.2-17" data-mini-rdoc="scam::logLik.gam">logLik.gam</a></code> of the <code>mgcv</code> package.
The documentation below is similar to that of object <code><a href="/link/logLik.gam?package=scam&version=1.2-17" data-mini-rdoc="scam::logLik.gam">logLik.gam</a></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

logLik.scam function

<dl>
 
<dt>object</dt>
<dd>fitted model objects of class <code>scam</code> as produced by <code>scam()</code>.</dd><dt>...</dt>
<dd>unused in this case</dd>
 </dl>

Arguments

Function to extract the log-likelihood for a fitted <code>scam</code>
model (fitted by penalized likelihood maximization). 
Used by <code>AIC</code>.
The function is a clone of <code><a href='https://rdrr.io/pkg/mgcv/man/logLik.gam.html'>logLik.gam</a></code> of the <code>mgcv</code> package.
The documentation below is similar to that of object <code><a href='https://rdrr.io/pkg/mgcv/man/logLik.gam.html'>logLik.gam</a></code>.

Log likelihood for a fitted SCAM, for AIC — logLik.scam

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

<dt>...</dt>
<dd>unused in this case</dd>
 

</dl>

logLik.scam: Log likelihood for a fitted SCAM, for AIC

Description

Usage

Value

Arguments

Details

References

See Also