mini.roots

INTERNAL function to obtain square roots, <code>B[[i]]</code>, of the penalty matrices <code>S[[i]]</code>'s having as few
 columns as possible.

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

mini.roots function

<dl><dt>S</dt>
<dd>a list of penalty matrices, in packed form.</dd>
<dt>off</dt>
<dd>a vector where the i-th element is the offset for the i-th matrix. 
The elements in columns <code>1:off[i]</code> of <code>B[[i]]</code> will be equal to zero.</dd>
<dt>np</dt>
<dd>total number of parameters.</dd>
<dt>rank</dt>
<dd>here <code>rank[i]</code> is optional supplied rank of <code>S[[i]]</code>. Set <code>rank[i] &lt; 1</code>, or 
<code>rank=NULL</code> to estimate.</dd></dl>

Arguments

Simon N. Wood &lt;simon.wood@r-project.org&gt;.

Author

Obtain square roots of penalty matrices — mini.roots

<dl>

<dt>S</dt>
<dd>a list of penalty matrices, in packed form.</dd>


<dt>off</dt>
<dd>a vector where the i-th element is the offset for the i-th matrix. 
The elements in columns <code>1:off[i]</code> of <code>B[[i]]</code> will be equal to zero.</dd>


<dt>np</dt>
<dd>total number of parameters.</dd>


<dt>rank</dt>
<dd>here <code>rank[i]</code> is optional supplied rank of <code>S[[i]]</code>. Set <code>rank[i] &lt; 1</code>, or 
<code>rank=NULL</code> to estimate.</dd>

</dl>

mini.roots: Obtain square roots of penalty matrices

Description

Usage

Value

Arguments

Author