Matrix containing functional data collected by row
theta
Vector containing the coefficients of \(\theta\) in a B-spline basis, so that length(theta)=order.Bspline+nknot.theta
order.Bspline
Order of the B-spline basis functions for the B-spline representation of \(\theta\). This is the number of coefficients in each piecewise polynomial segment. The default is 3.
nknot.theta
Number of regularly spaced interior knots of the B-spline basis. The default is 3.
range.grid
Vector of length 2 containing the range of the discretisation of the functional data. If range.grid=NULL, then range.grid=c(1,p) is considered, where p is the discretisation size of data (i.e. ncol(data)).
nknot
Number of regularly spaced interior knots for the B-spline representation of the functional data. The default value is (p - order.Bspline - 1)%/%2.
Novo S., Aneiros, G., and Vieu, P., (2019) Automatic and location-adaptive estimation in functional single--index regression. Journal of Nonparametric Statistics, 31(2), 364--392, tools:::Rd_expr_doi("https://doi.org/10.1080/10485252.2019.1567726").