I'm trying to pull diagnostics for 3 models at once using the accuracy() function from fabletools. I get this error:
Error in accuracy.default(rec_fore, df) :
First argument should be a forecast object or a time series.
rec_fore is a tbl_ts. From the online documentation, I believe this function should work on this class without needing to be coerced. Any tips? Code below..
# Train
rec_fit <- df_train %>%
model(
nnar_rec = NNETAR(rec, lambda = "auto"),
arima_rec = ARIMA(rec, stepwise = FALSE, approx = FALSE),
prophet_rec = prophet(rec ~ season(type = "multiplicative"))
)
# Forecast
rec_fore <- rec_fit %>%
forecast(h = 29) %>%
hilo(level = c(95)) %>%
unpack_hilo("95%")
# Diagnose
fabletools::accuracy(rec_fore, df)
This error is coming from the forecast::accuracy.default()
method.
To evaluate test-set forecast accuracy you would use the accuracy()
function with a <fable>
object.
Something like this should work:
rec_fit %>%
forecast(h = 29) %>%
accuracy(df)