tests/testthat/test-generics.R

In forecastHybrid: Convenient Functions for Ensemble Time Series Forecasts

# Unit tests on the generic function
numObs <- 100L
context("Testing generic functions")
set.seed(2345)
# Seaosnal data is required for the stlm model and will throw a warning
inputSeries <- 10 + rnorm(numObs)
expect_warning(hm <- hybridModel(y = inputSeries)) # nolint: implicit_assignment_linter
test_that("Testing summary and print methods", {
  # The generic methods should not throw an error
  expect_error(summary(hm), NA)
  expect_error(print(hm), NA)
  expect_true(is.hybridModel(hm))
})

test_that("Testing generics is.hybridModel(), fitted(), residuals(), and accuracy()", {
  inputSeries <- subset(USAccDeaths, end = 25)
  # add some seasonality so there are roots to plot in the arima model
  inputSeries <- 100 * (1:12) + USAccDeaths
  exampleModel <- hybridModel(inputSeries)
  expect_true(is.hybridModel(exampleModel))
  expect_length(fitted(exampleModel),
                length(residuals(exampleModel)))
  expect_length(fitted(exampleModel, individual = TRUE),
                length(residuals(exampleModel, individual = TRUE)))
  expect_error(accuracy(exampleModel), NA)
  expect_error(accuracy(exampleModel, individual = TRUE), NA)
  expect_error(plot(exampleModel, type = "fit", ggplot = FALSE), NA)
  expect_error(plot(exampleModel, type = "models", ggplot = FALSE), NA)
  expect_error(plot(exampleModel, type = "fit", ggplot = TRUE), NA)
  expect_error(plot(exampleModel, type = "models", ggplot = TRUE), NA)
})

test_that("Testing fitted and residual methods", {
  # The generic methods should not throw an error
  expect_error(fitted(hm), NA)
  expect_error(residuals(hm), NA)
  expect_error(fitted(hm, individual = TRUE), NA)
  expect_error(residuals(hm, individual = TRUE), NA)
  # There should be a fitted and residual for each observation in the input series
  expect_length(fitted(hm), numObs)
  expect_length(residuals(hm), numObs)
  expect_length(residuals(hm, individual = TRUE)$nnetar, numObs)
  expect_length(fitted(hm, individual = TRUE)$tbats, numObs)
  # TSP attributes should match when the input series is not a ts object
  expect_identical(tsp(residuals(hm)), tsp(fitted(hm)))
  # Residuals should be smaller than actual or fitted values
  hm <- hybridModel(wineind, model = "fs")
  expect_true(all(residuals(hm) < fitted(hm), na.rm = TRUE))
  expect_true(all(residuals(hm) < wineind, na.rm = TRUE))
  # TSP attributes should match when the input series is a ts object
  expect_identical(tsp(residuals(hm)), tsp(fitted(hm)))
  expect_identical(tsp(wineind), tsp(fitted(hm)))
})