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│ └─rlang::abort("I can't use NNETAR to forecast with missing values near the end of the series.")
│ └─rlang:::signal_abort(cnd, .file)
│ └─base::signalCondition(cnd)
└─dplyr (local) <fn>(<rlng_rrr>)
Finally, if TSLM() is used to fit that same model and with the same data, all works fine. And there is no missing values anywhere. 'Test' is 90 rows long.
Also, I am not sure if using lag() as above is best way to have NNETAR employ the variables from previous day.
Thanks in advance for assisting with this!
The text was updated successfully, but these errors were encountered:
I am getting this error that is identical to the error in this issue:
#326
I am able to fit this model as follows:
fit <- train |>
model(NNETAR(var1 ~ lag(var2, n = 1L) + lag(var3, n = 1L)))
However, use of that fit in fc and in a plot with this code will result in the error:
fit |>
forecast(new_data = test) |>
autoplot(train) +
autolayer(test3, close, colour = "orange")
A paste of what appears to be the critical part of the backtrace:
<fn>
(<rlng_rrr>
)Finally, if TSLM() is used to fit that same model and with the same data, all works fine. And there is no missing values anywhere. 'Test' is 90 rows long.
Also, I am not sure if using lag() as above is best way to have NNETAR employ the variables from previous day.
Thanks in advance for assisting with this!
The text was updated successfully, but these errors were encountered: