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Implements Leave-Future-Out Cross-Validation for time series models using forward-mode validation with Pareto-Smoothed Importance Sampling (PSIS) approximation to reduce computational cost. Supports both exact (always refit) and approximate methods. - lfo_cv.py: Main LFO-CV function with approx/exact methods - helper_lfo_cv.py: Helper functions for input validation, step computation, and result combination
Exports lfo_cv at package level and adds LFO-CV support to compare() function with proper validation to prevent comparing LFO-CV with incompatible methods (LOO-CV, K-fold-CV). - __init__.py files: Export lfo_cv function - compare.py: Add LFO-CV validation in _calculate_ics
Adds mock SamplingWrapper fixtures for LFO-CV testing along with comprehensive unit tests for main function and helper utilities. - conftest.py: LFO-CV fixtures (data_with_time, mock_lfo_wrapper, etc.) - test_lfo_cv.py: Unit tests for lfo_cv function - test_helper_lfo_cv.py: Unit tests for helper functions
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@jordandeklerk I initiated a PR. I'm also very busy, but wanted to get past the "empty page" blocker and have a start for the PR :) |
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Show files changed (16 files in total): 📝 15 modified | ➕ 0 added | ➖ 1 deleted
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Awesome, I will take a look soon! |
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This is a work in progress PR for adding approximate leave-future-out cross validation (LFO-CV) using pareto-smoothed importance sampling (PSIS).
The current implementation was planned by me and mostly implemented by Agentic assistance. I still need to personally go through it in detail.
This PR is related to issue #177