A special <code>smooth.construct</code> method function for creating tensor product smooths from any
combination of single penalty marginal smooths.

smooth.construct.tensor.smooth.spec

Generalized additive (mixed) models, some of their extensions and
other generalized ridge regression with multiple smoothing
parameter estimation by (Restricted) Marginal Likelihood,
Cross Validation and similar, or using iterated nested Laplace
approximation for fully Bayesian inference. See Wood (2025)
<doi:10.1146/annurev-statistics-112723-034249> 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

smooth.construct.tensor.smooth.spec function

Tensor product smoothing constructor — smooth.construct.tensor.smooth.spec

<dl>
 
<dt>object</dt>
<dd>a smooth specification object of class <code>tensor.smooth.spec</code>, 
 usually generated by a term like <code>te(x,z)</code> in a <code>gam</code> model formula</dd>


<dt>data</dt>
<dd>a list containing just the data (including any <code>by</code> variable) required by this term, 
 with names corresponding to <code>object$term</code> (and <code>object$by</code>). The <code>by</code> variable 
 is the last element.</dd>
 

<dt>knots</dt>
<dd>a list containing any knots supplied for basis setup --- in same order and with same names as <code>data</code>. 
 Can be <code>NULL</code>. See details for further information.</dd>


</dl>

Arguments

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

smooth.construct.tensor.smooth.spec: Tensor product smoothing constructor

Description

Usage

Arguments

Value

Details

References

See Also

Examples