A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.
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Input contains NaN for a non NaN data #573
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tifa64 opened 6 months ago
Describe the question you have
Hello maintainers, I want to understand why this scenario happens, I have the following timeseries
Which yields this ts
and when I try and fit the model, it yields these information:
and when I try and fit the model, it yields these information:
Then I try to predict
and shows below error
However when I increase the data by one data point
or when I change to these values
or when setting the
seasonal
parameter toTrue
for the same exact dataThe model returned is
ARIMA(0,0,0)(0,0,0)[0] intercept
and the predictions are fine without errorsAnother work around is to put a guradrail of maximum p, q, d to be 1 and it also works.
Can you help me understand why this happens? Is placing a guardrail the correct way to fix this?
Thank you in advance :)
Here is a video of a cute Otter as a digital bribe: https://www.youtube.com/watch?v=8O8iEz2p7rQ Can you help me understand this behaviour?
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