ARIMA forecast time series

Machine Learning and Modeling
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Hello all,

I have used the forecast::auto.arima() function to make an ARIMA model about a time series.

Rplot1.pdf (5.8 KB) Rplot2.pdf (19.9 KB) Rplot3.pdf (6.7 KB)

I have followed the great book by Rob J. Hyndman and George Athanasopoulos (2018) Forecasting: principles and practice, 2nd edition, OTexts: Melbourne, Australia. Forecasting: Principles and Practice (2nd ed). However, I am not sure about the results of my model, given that the distribution of residuals does not look much like a normal distribution, and that some of the inverse roots lie very close to the complex unit circle.

Any idea what might be happening?

Thanks in advance for any help!

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