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# A unit test for forecast.R
if (require(testthat)) {
test_that("tests for findfrequency()", {
expect_true(frequency(airmiles) == findfrequency(as.numeric(airmiles)))
expect_false(frequency(wineind) == findfrequency(as.numeric(wineind)))
expect_true(frequency(woolyrnq) == findfrequency(as.numeric(woolyrnq)))
expect_true(frequency(gas) == findfrequency(as.numeric(gas)))
})
test_that("tests forecast.ts()", {
fc1 <- as.numeric(forecast(as.numeric(airmiles), find.frequency = TRUE)$mean)
fc2 <- as.numeric(forecast(airmiles)$mean)
expect_true(all(fc1 == fc2))
})
test_that("tests summary.forecast() and forecast.forecast()", {
WWWusageforecast <- forecast(WWWusage)
expect_output(print(summary(WWWusageforecast)), regexp = "Forecast method:")
expect_true(all(predict(WWWusageforecast)$mean == forecast(WWWusageforecast)$mean))
})
# test_that("tests plot.forecast()", {
# # Fit several types of models for plotting
# batsmod <- bats(woolyrnq)
# nnetmod <- nnetar(woolyrnq)
# tslmmod <- tslm(woolyrnq ~ trend + season)
# nnetfc<- forecast(nnetmod)
# batsfc <- forecast(batsmod)
# tslmfc <- forecast(tslmmod)
# skip_on_travis()
# # Plot the forecasts
# expect_that(plot(nnetfc), not(throws_error()))
# expect_that(plot(batsfc), not(throws_error()))
# expect_that(plot(batsfc, shaded = FALSE), not(throws_error()))
# expect_that(plot(tslmfc, PI = FALSE), not(throws_error()))
# expect_that(plot(forecast(tslmmod, h = 0)), not(throws_error()))
# })
}
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