influence.gam

Extracts the leading diagonal of the influence matrix (hat
matrix) of a fitted <code>gam</code> object.

models

regression

smooth

Generalized additive (mixed) models, some of their extensions and
other generalized ridge regression with multiple smoothing
parameter estimation by (Restricted) Marginal Likelihood,
Generalized Cross Validation and similar, or using iterated
nested Laplace approximation for fully Bayesian inference. See
Wood (2017) <doi:10.1201/9781315370279> for an overview.
Includes a gam() function, a wide variety of smoothers, 'JAGS'
support and distributions beyond the exponential family.

Simon Wood

mgcv

Mixed GAM Computation Vehicle with Automatic Smoothness
Estimation

influence.gam function

<dl>
 
<dt>model</dt>
<dd>fitted model objects of class <code>gam</code> as produced by <code>gam()</code>.</dd><dt>...</dt>
<dd>un-used in this case</dd>
 </dl>

Arguments

Simon N. Wood <a href="/link/simon.wood%40r-project.org?package=mgcv&version=1.9-1" data-mini-rdoc="mgcv::simon.wood@r-project.org">simon.wood@r-project.org</a>

Author

Extract the diagonal of the influence/hat matrix for a GAM — influence.gam

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

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

</dl>

Simon N. Wood <a href='mailto:simon.wood@r-project.org'>simon.wood@r-project.org</a>

influence.gam: Extract the diagonal of the influence/hat matrix for a GAM

Description

Usage

Value

Arguments

Author

Details

See Also