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

In dual.spls: Dual Sparse Partial Least Squares Regression

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

  n <- 100
  p <- 50
  nondes <- 20
  sigmaondes <- 0.5
  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.lasso(X=X,y=y,ncp=ncp,ppnu=ppnu,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)

})