R: Orthogonal Spline Design Matrix

spl {MCMCglmm} | R Documentation

## Orthogonal Spline Design Matrix

### Description

Orthogonal Spline Design Matrix

### Usage

    spl(x,  k=10, knots=NULL, type="LRTP")

### Arguments

`x` | a numeric covariate
`k` | integer, defines knot points at the 1:k/(k+1) quantiles of x
`knots` | vector of knot points
`type` | type of spline - currently only low-rank thin-plate ("LRTP") are implemented

### Value

Design matrix post-multiplied by the inverse square root of the penalty matrix

### Author(s)

Jarrod Hadfield j.hadfield@ed.ac.uk

### Examples

    ## Not run:
    x<-rnorm(100)
    y<-x^2+cos(x)-x+0.2*x^3+rnorm(100)
    plot(y~x)
    lines((x^2+cos(x)-x+0.2*x^3)[order(x)]~sort(x))

    dat<-data.frame(y=y, x=x)

    m1<-MCMCglmm(y~x, random=~idv(spl(x)), data=dat, pr=TRUE, verbose=FALSE) # penalised smoother
    m2<-MCMCglmm(y~x+spl(x),data=dat,  verbose=FALSE)                        # non-penalised

    pred1<-(cbind(m1$X,m1$Z)%*%colMeans(m1$Sol))@x
    pred2<-(cbind(m2$X)%*%colMeans(m2$Sol))@x

    lines(pred1[order(x)]~sort(x), col="red")
    lines(pred2[order(x)]~sort(x), col="green")

    m1$DIC-mean(m1$Deviance)  # effective number of parameters < 13
    m2$DIC-mean(m2$Deviance)  # effective number of parameters ~ 13

    ## End(Not run)

[Package MCMCglmm version 2.32 Index]