test_that("nrm_multivariate returns correct structure", {
  data(nrm_example, package = "NRMstatsML")
  mv <- nrm_multivariate(nrm_example,
          formula = crop_yield ~ N + P + K + rainfall)
  expect_s3_class(mv, "nrm_multivariate")
  expect_true(is.numeric(mv$r_squared))
  expect_true(mv$r_squared >= -1 && mv$r_squared <= 1)
  expect_true(is.matrix(mv$coefficients))
})

test_that("nrm_multivariate with scale = FALSE still fits", {
  data(nrm_example, package = "NRMstatsML")
  mv <- nrm_multivariate(nrm_example,
          formula = crop_yield ~ N + rainfall, scale = FALSE)
  expect_false(mv$scaled)
  expect_s3_class(mv$model, "lm")
})

test_that("nrm_multivariate errors when formula is not a formula", {
  data(nrm_example, package = "NRMstatsML")
  expect_error(nrm_multivariate(nrm_example, formula = "crop_yield ~ N"),
               "must be a formula")
})

test_that("nrm_pls returns model and rmsep", {
  data(nrm_example, package = "NRMstatsML")
  pl <- nrm_pls(nrm_example,
                formula = crop_yield ~ N + P + K + rainfall + soil_OC,
                ncomp = 2)
  expect_s3_class(pl, "nrm_pls")
  expect_true(pl$ncomp >= 1)
  expect_true(is.numeric(pl$rmsep))
})