R: Creates a model using penalized smoothing splines

rb {SpatialExtremes} | R Documentation

## 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)

[Package SpatialExtremes version 2.0-5 Index]