# generate data
set.seed(5732)
x1 <- runif(100) 
x2 <- runif(100) 
x3 <- runif(100) 
y <- 10*sin(pi*x2)+exp(3*x3)+5*cos(2*pi*(x1-x2))+3*rnorm(x1)

# fit linear spline model and obtain diagnostics
fit <- ssanova(y~x1*x2*x3-x1:x2:x3,type="linear")
sum.fit <- summary(fit,diagnostics=TRUE)
round(sum.fit$kappa,2)
round(sum.fit$pi,2)
round(sum.fit$cosines,2)

# fit cubic spline model and obtain diagnostics
fit.new.c <- ssanova(y~x1*x2+x3,type="cubic")
sum.new.c<-summary(fit.new.c,TRUE)
round(sum.new.c$pi,2)
round(sum.new.c$cos,2)