tests/testthat/test-ols.R

In kcmeans: Conditional Expectation Function Estimation with K-Conditional-Means

# ols ==========================================================================
test_that("ols returns output of correct types", {
  # Simulate small dataset and fit ols
  X <- matrix(rnorm(100*3), 100, 3)
  y <- 1 + X %*% c(-1, 1, 0) + rnorm(100)
  mdl_fit <- ols(y, X, const = T)
  # Check output with expectations
  expect_equal(dim(mdl_fit$coef), c(1+ncol(X), 1)) # Return a vector
})#TEST_THAT

test_that("predict.ols returns fitted values", {
  # Simulate small dataset and fit ols
  X1 <- matrix(rnorm(100*3), 100, 3); X2 <- matrix(rnorm(100*3), 100, 3)
  y <- 1 + X1 %*% c(-1, 1, 0) + rnorm(100)
  mdl_fit <- ols(y, X1, const = T, w = runif(100))
  # Check in- and out-of-sample fitted values
  expect_equal(predict(mdl_fit), cbind(1, X1) %*% mdl_fit$coef)
  expect_equal(predict(mdl_fit, newdata = X2), cbind(1, X2) %*% mdl_fit$coef)
})#TEST_THAT

# wls ==========================================================================
test_that("wls returns output of correct types", {
  # Simulate small dataset and fit ols
  X <- matrix(rnorm(100*3), 100, 3)
  y <- 1 + X %*% c(-1, 1, 0) + rnorm(100)
  mdl_fit <- ols(y, X, const = T, w = runif(100))
  # Check output with expectations
  expect_equal(dim(mdl_fit$coef), c(1+ncol(X), 1)) # Return a vector
})#TEST_THAT