The thin plate spline penalties give zero penalty to some
functions. The space of these functions is spanned by a set of
polynomial terms. null.space.dimension
finds the dimension of this space, \(M\), given
the number of covariates that the smoother is a function of, \(d\),
and the order of the smoothing penalty, \(m\). If \(m\) does not
satisfy \(2m>d\) then the smallest possible dimension
for the null space is found given \(d\) and the requirement that
the smooth should be visually smooth.
null.space.dimension(d,m)
is a positive integer - the number of variables of which the t.p.s. is a function.
a non-negative integer giving the order of the penalty functional, or signalling that the default order should be used.
An integer (array), the null space dimension \(M\).
Thin plate splines are only visually smooth if the order of the wiggliness penalty, \(m\), satisfies \(2m > d+1\). If \(2m<d+1\) then this routine finds the smallest \(m\) giving visual smoothness for the given \(d\), otherwise the supplied \(m\) is used. The null space dimension is given by:
\(M=(m+d-1)!/(d!(m-1)!)\)
which is the value returned.
Wood, S.N. (2003) Thin plate regression splines. J.R.Statist.Soc.B 65(1):95-114
# NOT RUN {
require(mgcv)
null.space.dimension(2,0)
# }
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