# generate data and fit the model
set.seed(5732)
x <- (0:100)/100
y <- 1 + 3 * sin(2*pi*x) + 2 * (x>.7) + rnorm(x)
part.fit <- ssanova(y~x,partial=as.numeric(x>.7),ext=0)

# evaluate the fit and plot
new <- data.frame(x=x,partial=as.numeric(x>.7))
est <- predict(part.fit,new,se=TRUE)
plot(x,y)
lines(x,1+3*sin(2*pi*x)+2*(x>.7),col=6)
lines(x,est$fit,col=4)
lines(x,est$fit+1.96*est$se,col=5)
lines(x,est$fit-1.96*est$se,col=5)