rb: Creates a model using penalized smoothing splines

In SpatialExtremes: Modelling Spatial Extremes

Creates a model using penalized smoothing splines

Description

Creates a model using penalized smoothing splines using radial basis functions

Usage

rb(..., knots, degree, penalty)

Arguments

...	The explicative variables for which the spline is based on.
knots	The coordinates of knots. See section details.
degree	Numeric. The degree of the spline.
penalty	Numeric. The penalty coefficient.

Details

If one explicative variable is given in "...", the knots should be a numeric vector. Otherwise, knots should be a matrix with the same number of column and covariates.

Value

A list giving all the required information to fit a penalized smoothing spline:

dsgn.mat	The design matrix.
pen.mat	The penalization matrix.
degree	The degree of the smoothing spline.
penalty	The penalty of the smoothing spline.
knots	The knots of the smoothing spline.
data	The explicative variables (e.g. covariates).
call	How was the rb function was called?

Warning

This function is not supposed to be called directly. rb is supposed to be embedded in a R formula.

Author(s)

Mathieu Ribatet

See Also

fitmaxstab

Examples

n.site <- 30
locations <- matrix(runif(2*n.site, 0, 10), ncol = 2)
colnames(locations) <- c("lon", "lat")
knots <- quantile(locations[,2], 1:5/6)

form <- y ~ rb(lat, knots = knots, degree = 3, penalty = .5)

SpatialExtremes documentation built on April 19, 2022, 5:06 p.m.