tests/testthat/test-accuracy.R

In forecast: Forecasting Functions for Time Series and Linear Models

# A unit test for accuracy() function
if (require(testthat)) {
  test_that("tests for a non-forecast object (input)", {
    expect_error(accuracy(USAccDeaths))
  })

  test_that("tests for dimension (output)", {
    train <- window(USAccDeaths, start = c(1973, 1), end = c(1976, 12))
    test <- window(USAccDeaths, start = c(1977, 1))
    fcasts <- forecast(train, h = 6)
    expect_identical(dim(accuracy(fcasts)), c(1L, 7L))
    expect_identical(dim(accuracy(fcasts, test)), c(2L, 8L))
    expect_false(
      all(dim(accuracy(fcasts, test, test = 1:2)) == dim(accuracy(fcasts, test)))
    )
    expect_identical(accuracy(fcasts, test = 1:length(train)), accuracy(fcasts))
  })
  test_that("tests for accuracy (output)", {
    # Test arima
    fitarima <- Arima(USAccDeaths, order = c(0, 1, 1), seasonal = c(0, 1, 1))
    accuracyarima <- accuracy(fitarima)[1, "RMSE"]
    accuracyarimasim <- accuracy(Arima(simulate(fitarima, seed = 123), order = c(0, 1, 0), seasonal = c(0, 0, 1)))[1, "RMSE"]
    expect_lt(accuracyarima, accuracyarimasim)
    # Test ets
    fitets <- ets(AirPassengers, model = "MAM", damped = TRUE)
    accuracyets <- accuracy(fitets)[1, "RMSE"]
    accuracyetssim <- accuracy(ets(simulate(fitets, seed = 123), model = "MAM", damped = TRUE))[1, "RMSE"]
    expect_lt(accuracyets, accuracyetssim)
    # Test lm
    month <- factor(rep(1:12, 14))
    fitlm <- lm(wineind[1:168] ~ month)
    accuracylm <- accuracy(fitlm)[1, "RMSE"]
    accuracylmsim <- accuracy(lm(simulate(fitlm, seed = 123)[, 1] ~ month))[1, "RMSE"]
    expect_gt(accuracylm, accuracylmsim)
  })
}