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[ENH] enhance naive forecaster with new strategies #2869

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Reference Issues/PRs

Fixes #2823.

What does this implement/fix? Explain your changes.

  1. New strategies for the naive forecaster, including mean and seasonal last, are added.
  2. test_naive.py for testing the naive forecaster is added.

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

No.

Any other comments?

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@aeon-actions-bot aeon-actions-bot bot added enhancement New feature, improvement request or other non-bug code enhancement forecasting Forecasting package labels Jun 2, 2025
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Thank you for contributing to aeon

I have added the following labels to this PR based on the title: [ $\color{#FEF1BE}{\textsf{enhancement}}$ ].
I have added the following labels to this PR based on the changes made: [ $\color{#31FCCD}{\textsf{forecasting}}$ ]. Feel free to change these if they do not properly represent the PR.

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Comment on lines 25 to 34
Parameters
----------
strategy : str, default="last"
The forecasting strategy to use.
Options: "last", "mean", "seasonal_last".
seasonal_period : int, default=1
The seasonal period to use for the "seasonal_last" strategy.
E.g., 12 for monthly data with annual seasonality.
horizon : int, default=1
The number of time steps ahead to forecast.
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This should be in the class docstring.

Comment on lines 12 to 18
Strategies:
- "last": predicts the last seen value in training for all horizon steps.

- "mean": predicts the mean of the training series for all horizon steps.

- "seasonal_last": predict the last season value seen in the training series.
Returns np.nan if the effective seasonal data is empty.
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Include this in the Parameter documentation instead

Comment on lines 38 to 39
self._fitted_scalar_value_ = None # For 'last' and 'mean' strategies
self._fitted_last_season_ = np.array([]) # For 'seasonal_last', init as empty
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do this in _fit ideally

Comment on lines 8 to 10
def sample_data():
"""Pytest fixture for sample time series data."""
return np.array([10, 20, 30, 40, 50])
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Don't think this is needed, can just create the array in each test.

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[ENH] Refactor and improve NaiveForecaster
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