This function returns the marginal model matrices and the list of penalty matrices
for the tensor product bivariate smooth with the single concavity or convexity restriction 
along the second covariate. The marginal smooth functions of both covariates are constructed using the B-spline basis functions.

marginal.matrices.tescv.ps

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

marginal.matrices.tescv.ps function

Constructs marginal model matrices for "tescv" and "tescx" bivariate smooths in case of B-splines basis functions for both unconstrained marginal smooths — marginal.matrices.tescv.ps

<dl>

 <dt>x</dt>
<dd>A numeric vector of the values of the first covariate at which to evaluate the B-spline marginal functions.
 The values in <code>x</code> must be between <code>xk[m[1]+2]</code> and
 <code>xk[length(xk) - m[1] - 1]</code>.</dd>


 <dt>z</dt>
<dd>A numeric vector of the values of the second covariate at which to evaluate the B-spline marginal functions.
 The values in <code>z</code> must be between <code>zk[m[2]+2]</code> and
 <code>zk[length(zk) - m[2] - 1]</code>.</dd>


 <dt>xk</dt>
<dd>A numeric vector of knot positions for the first covariate, <code>x</code>, with non-decreasing values.</dd>


 <dt>zk</dt>
<dd>A numeric vector of knot positions for the second covariate,<code>z</code>, with non-decreasing values.</dd>


 <dt>m</dt>
<dd>A pair of two numbers where <code>m[i]+1</code> denotes the order of the basis of the \(i^{th}\) marginal smooth
 (e.g. <code>m[i] = 2</code> for a cubic spline.)</dd>
 

 <dt>q1</dt>
<dd>A number denoting the basis dimension of the first marginal smooth.</dd>


 <dt>q2</dt>
<dd>A number denoting the basis dimension of the second marginal smooth.</dd>


</dl>

Arguments

Natalya Pya &lt;nat.pya@gmail.com&gt;

Author

Constructs marginal model matrices for "tescv" and "tescx" bivariate smooths in case of B-splines basis functions for both unconstrained marginal smooths

marginal.matrices.tescv.ps: Constructs marginal model matrices for "tescv" and "tescx" bivariate smooths in case of B-splines basis functions for both unconstrained marginal smooths

Description

Usage

Arguments

Value

Details

References

See Also