tests/testthat/test-d.spls.ridge.R

In dual.spls: Dual Sparse Partial Least Squares Regression

test_that("d.spls.ridge works", {

n <- 200
p <- 100
nondes <- 150
sigmaondes <- 0.01
data=d.spls.simulate(n=n,p=p,nondes=nondes,sigmaondes=sigmaondes)

X <- data$X
y <- data$y

#fitting the model
ncp=10
ppnu=0.9
mod.dspls <- d.spls.ridge(X=X,y=y,ncp=ncp,ppnu=ppnu,nu2=0.05,verbose=TRUE)
n <- dim(X)[1]
p <- dim(X)[2]

# dimension testing
expect_equal(dim(mod.dspls$scores), c(n,ncp))
expect_equal(length(mod.dspls$intercept), ncp)
expect_equal(dim(mod.dspls$Bhat), c(p,ncp))
expect_equal(dim(mod.dspls$loadings), c(p,ncp))
expect_equal(dim(mod.dspls$fitted.values), c(n,ncp))

# residuals
expect_equal(mod.dspls$residuals, y-mod.dspls$fitted.values, tolerance = 1e-5)

# mean of X
expect_equal(apply(X, 2, mean), mod.dspls$Xmean, tolerance = 1e-5)

# zerovar
for (i in 2:ncp)
{
  expect_gt(mod.dspls$zerovar[i-1],mod.dspls$zerovar[i]-1)
}
expect_lt(mod.dspls$zerovar[1], ppnu*p+1)})