Improve statistical forecasting validation, selection, and monitoring

[bmfmancini]

• Prevent leakage and require complete common rolling-origin validation
• Reserve final holdouts for evaluating the selected procedure
• Unify fitting and fallback selection across forecasting models
• Improve prediction intervals and residual diagnostics
• Compare ensembles, transformations, and recent training windows
• Add dynamic regression, intermittent demand, and quantile forecasting
• Preserve calendar gaps and support explicit aggregation
• Store issued forecasts and monitor accuracy against actuals
• Add documentation, reproducible benchmarks, and regression tests

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[sonarqubecloud]

Quality Gate failed

Failed conditions
D Security Rating on New Code (required ≥ A)
C Reliability Rating on New Code (required ≥ A)

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