cSplineDes {mgcv} R Documentation

## Evaluate cyclic B spline basis

### Description

Uses splineDesign to set up the model matrix for a cyclic B-spline basis.

### Usage

cSplineDes(x, knots, ord = 4, derivs=0)


### Arguments

 x covariate values for smooth. knots The knot locations: the range of these must include all the data. ord order of the basis. 4 is a cubic spline basis. Must be >1. derivs order of derivative of the spline to evaluate, between 0 and ord-1. Recycled to length of x.

### Details

The routine is a wrapper that sets up a B-spline basis, where the basis functions wrap at the first and last knot locations.

### Value

A matrix with length(x) rows and length(knots)-1 columns.

### Author(s)

Simon N. Wood simon.wood@r-project.org

cyclic.p.spline

### Examples

 require(mgcv)
## create some x's and knots...
n <- 200
x <- 0:(n-1)/(n-1);k<- 0:5/5
X <- cSplineDes(x,k) ## cyclic spline design matrix
## plot evaluated basis functions...
plot(x,X[,1],type="l"); for (i in 2:5) lines(x,X[,i],col=i)
## check that the ends match up....
ee <- X[1,]-X[n,];ee
tol <- .Machine$double.eps^.75 if (all.equal(ee,ee*0,tolerance=tol)!=TRUE) stop("cyclic spline ends don't match!") ## similar with uneven data spacing... x <- sort(runif(n)) + 1 ## sorting just makes end checking easy k <- seq(min(x),max(x),length=8) ## create knots X <- cSplineDes(x,k) ## get cyclic spline model matrix plot(x,X[,1],type="l"); for (i in 2:ncol(X)) lines(x,X[,i],col=i) ee <- X[1,]-X[n,];ee ## do ends match?? tol <- .Machine$double.eps^.75
if (all.equal(ee,ee*0,tolerance=tol)!=TRUE)
stop("cyclic spline ends don't match!")


[Package mgcv version 1.9-0 Index]