ncs: Tool to build the basis matrix and the penalty matrix of natural cubic splines.
Description
ncs builds the basis matrix and the penalty matrix to approximate a smooth function using a natural cubic spline.
Usage
ncs(xx, lambda, nknots, all.knots)
Value
xx
the explanatory variable \(xx\) with the following attributes: set of knots, basis matrix, penalty matrix, smoothing parameter
(if it was specified), and other interest matrices.
Arguments
xx
the explanatory variable.
lambda
an optional positive value that represents the smoothing parameter value.
nknots
an optional positive integer that represents the number of knots of the natural cubic spline. Default is \(m=[n^{\frac{1}{3}}]+3\).
The knots are located at the quantiles of order \(0/(m-1),1/(m-1),\ldots,(m-1)/(m-1)\) of xx.
all.knots
logical. If TRUE, the set of knots and the set of different values of \(xx\) coincide. Default is FALSE.
Author
Luis Hernando Vanegas <hvanegasp@gmail.com> and Gilberto A. Paula
References
Lancaster, P. and Salkauskas, K. (1986) Curve and Surface Fitting: an introduction. Academic Press, London.
Green, P.J. and Silverman, B.W. (1994) Nonparametric Regression and Generalized Linear Models, Boca Raton: Chapman and Hall.