tests/testthat/test_method_predict.R

In JENScoding/York: York's regression of X and Y-variables with correlated errors

test_that("Test implementation of predict.york method", {
  ## Input from Table I and Table II in York 1966
  x <- c(0,0.9, 1.8, 2.6, 3.3, 4.4, 5.2, 6.1, 6.5, 7.4)
  y <- c(5.9, 5.4, 4.4, 4.6, 3.5, 3.7, 2.8, 2.8, 2.4, 1.5)

  weights_y = c(1, 1.8, 4, 8, 20, 20, 70, 70, 1e+2, 5e+2)
  weights_x = c(1e+3, 1e+3, 5e+2, 8e+2, 2e+2, 8e+1, 6e+1, 2e+1, 1.8, 1)

  ## Test
  first <- york(x, y, weights_x = weights_x, weights_y = weights_y,
                r_xy_errors = 0, approx_solution = TRUE)
  new <- c(2,3,4,3.6)
  expect_error(predict.york(first, new), NA)
  expect_error(predict(first, new), NA)

  second <- predict(first, new)
  expect_true(all(round(second$prediction[,2], 4) == c(4.5080, 4.0308, 3.5535,
                                                       3.7444)))
  expect_true(all(colnames(second$prediction) == c("x", "predict_y")))

  new <- data.frame(c(2,3,4,3.6), fix.empty.names = FALSE)
  second <- predict.york(first, new)
  expect_true(all(round(second$prediction[,2], 4) == c(4.5080, 4.0308, 3.5535, 3.7444)))
  expect_true(all(colnames(second$prediction) == c("x", "predict_y")))
})