tests/testthat/test-ets.R

In pli2016/forecast: Forecasting Functions for Time Series and Linear Models

# A unit test for ets function
if(require(testthat))
{
	context("Tests on input")
	test_that("tests for some arguments in ets", {
	  fit <- ets(wineind, model = "ZZM")
	  comp <- paste0(fit$components[1:3], collapse = "")
	  expect_that(comp, equals("MAM"))
	})

	test_that("tests for some arguments in ets", {
	  fit <- ets(wineind, model = "MAM", alpha = 0.1611)
	  expect_that(as.numeric(fit$par["alpha"]), equals(0.1611))
	})

	test_that("refit ets model to new data", {
	  fit <- ets(wineind, model = "MAM", alpha = 0.1611)
	  parnames <- c("alpha","beta","gamma")
	  par <- fit$par[parnames]
	  expect_identical(ets(wineind, model=fit, alpha=0.1611)$par[parnames], par)
	  expect_identical(ets(wineind, model=fit, alpha=0.1611, beta=NA)$par[parnames],par)
	  expect_identical(ets(wineind, model=fit, alpha=0.1611, gamma=NA)$par[parnames],par)
	  expect_identical(ets(wineind, model=fit, alpha=0.1611, phi=NA)$par[parnames],par)
	  expect_identical(ets(wineind, model=fit, alpha=0.1611, use.initial.values=TRUE)$par,fit$par)
	})

	test_that("class methods for ets work", {
	  fit <- ets(wineind, model = "MAM", alpha = 0.1611)
	  expect_output(summary(fit),"Smoothing parameters")
	  expect_equal(length(coef(fit)), 16L)
	  expect_lt(abs(logLik(fit) + 1802.9586023), 1e-5)
	  plot(fit)
	})

	test_that("test ets() for errors", {
	  expect_warning(ets(taylor))
	  fit1<-ets(airmiles, lambda = 0.15, biasadj=FALSE)
	  expect_gt(fit1$par["alpha"], 0.96)
	  fit2<-ets(airmiles, lambda = 0.15, biasadj = TRUE)
	  expect_gt(fit2$par["alpha"], 0.96)
	  expect_false(identical(fit1$fitted, fit2$fitted))
	  expect_error(ets(taylor, model = "ZZA"))
	})

	test_that("forecast.ets()", {
	  fit<-ets(airmiles, lambda = 0.15, biasadj = TRUE)
	  fcast1 <- forecast(fit, PI=FALSE)
	  expect_true(is.null(fcast1$upper) & is.null(fcast1$lower))
	  fcast1 <- forecast(fit, biasadj=FALSE)
	  fcast2 <- forecast(fit, biasadj=TRUE)
	  expect_false(identical(fcast1$mean, fcast2$mean))
	  fcast <- forecast(fit, simulate=TRUE)
	  expect_true(!is.null(fcast$upper) & !is.null(fcast$lower))
	  expect_true(all(fcast$upper > fcast$lower))
	})
}