cSplineDes: Evaluate cyclic B spline basis

In mgcv: Mixed GAM Computation Vehicle with Automatic Smoothness Estimation

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 [e-mail]

See Also

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!")

mgcv documentation built on May 29, 2024, 4:34 a.m.