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## help functions
bs.design<-function(x, xl, xr, spline.degree, nbasis, comp = NULL)
{
## generate a B-Spline-Matrix with equidistant knots (code by Thomas Kneib & Andreas Groll):
## x are the positions where spline to be evaluated
## xl, xr intervall boundaries where spline functions are relevant
xmin<-xl-(xr-xl)/100
xmax<-xr+(xr-xl)/100
dx<-(xmax-xmin)/(nbasis-3)
knots<-seq(xmin-spline.degree*dx,xmax+spline.degree*dx,by=dx)
B<-splines::spline.des(knots,x,spline.degree+1,outer.ok = TRUE)$design
if(is.null(comp))
{
return(B)
}else{
return(B[,comp])
}
}
########
mirror <- function(x,low.tri)
{
x[low.tri] <- t(x)[low.tri]
return(x)
}
#############
penal.fct <- function(x,K)
{
sqrt(t(x) %*% (K %*% x))
}
#############
factor.test <- function(x)
{
substr(x,1,9)=="as.factor"
}
#############
penal.fct.inv <- function(x,K,c.app)
{
(as.numeric(t(x) %*% (K %*% x))+c.app)^(-0.5)
}
#############
eucl.norm <- function(x)
{
sqrt(sum(x^2))
}
#############
count.levels <- function(x)
{
nlevels(x)
}
#############
center.fct <- function(fit.vec,mean.vec,sd.vec,nbasis,m, standardize = TRUE, center = TRUE)
{
if(!center)
mean.vec <- rep(0,length(mean.vec))
if(!standardize)
sd.vec <- rep(1,length(sd.vec))
Delta.base.retrans <- c(1,-mean.vec/sd.vec) %*% t(matrix(fit.vec[1:(nbasis*(m+1))],nbasis,m+1))
return(Delta.base.retrans)
}
############
int.approx <- function(z,time.grid,B,nbasis,alpha)
{
index <- time.grid<z[1]
diff(time.grid[1:2]) * sum(exp(B[index,] %*% (alpha * rep(z[2:length(z)],each=nbasis))))
}
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