[ENH] Make fit in ARIMA iterative_forecast optional #3078

[Lucky-Lodhi2004]

Reference Issues/PRs

Fixes #3078

####Updated Files

• aeon/forecasting/stats/_arima.py

What does this implement/fix? Explain your changes.

Quoting @JoaquinAmatRodrigo

The current implementation of aeon.forecasting.stats.ARIMA.iterative_forecast includes fitting the forecaster as its first step.
If the ARIMA model has already been fitted, this additional fit step is unnecessary. All the required information for subsequent predictions is already stored in the fitted model.

For resolving this issue, I have not added any module or method but just edited aeon/forecasting/stats/_arima.py . I have made following changes in iterative_forecast method of ARIMA class (line 210 of _arima.py).

def iterative_forecast(self, y, prediction_horizon, fit=True):
        if fit:
            self.fit(y)
        elif not self.is_fitted:
            raise ValueError(
                "Model must be fitted before calling iterative_forecast with fit=False."
            )

I added extra parameter 'fit' into the method iterative__forecast(). iterative_forecast will raise error if model isn't fitted before, and fitting can be set as true or false.

Does your contribution introduce a new dependency? If yes, which one?

No, my contribution does not introduce any new dependency

Any other comments?

I ran pytest on whole codebase and everything seems fine.

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