##### https://github.com/cran/sparseFLMM
Revision 3d1203b48f7c62e32d347f479e8b295770f2f806 authored by Jona Cederbaum on 11 September 2020, 11:20:02 UTC, committed by cran-robot on 11 September 2020, 11:20:02 UTC
1 parent 5f8586c
Tip revision: 3d1203b
make_summation_matrix.Rd
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/tri_constraint_constructor.R
\name{make_summation_matrix}
\alias{make_summation_matrix}
\title{Construct symmetry constraint matrix for bivariate symmetric smoothing.}
\usage{
make_summation_matrix(F)
}
\arguments{
\item{F}{number of marginal basis functions.}
}
\value{
A symmetry constraint matrix of dimension \eqn{F^2 x F(F+1)/2}.
}
\description{
This function can be used to construct a symmetry constraint matrix that imposes
a symmetry constraint on spline coefficients in symmetric bivariate smoothing problems and is especially
designed for constructing objects of the class "symm.smooth", see \code{\link[sparseFLMM]{smooth.construct.symm.smooth.spec}}.
}
\details{
Imposing a symmetry constraint to the spline coefficients in order to obtain a reduced coefficient vector is
equivalent to right multiplication of the bivariate design matrix
with the symmetry constraint matrix obtained with function \code{make_summation_matrix}.
The penalty matrix of the bivariate smooth needs to be adjusted to the reduced coefficient vector
by left and right multiplication with the symmetry constraint matrix.
This function is used in the constructor function \code{\link[sparseFLMM]{smooth.construct.symm.smooth.spec}}.
}
\references{
Cederbaum, Scheipl, Greven (2016): Fast symmetric additive covariance smoothing.
Submitted on arXiv.
}
\seealso{