Add Tweedie distribution - #3277
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Implement Tweedie distribution following PyTorch PR #171705, suitable for modeling non-negative data with exact zeros (insurance claims, rainfall, intermittent demand). Features: - Tweedie class extending torch.distributions.Distribution - Parameters: mu (mean), dispersion, power (in range 1-2) - Compound Poisson-Gamma sampling algorithm - Saddle-point approximation for log_prob (Dunn & Smyth 2005) - TweedieOutput class for use with GluonTS estimators (DeepAR, etc.) - Learnable mu, dispersion, and power parameters - Proper domain mapping via softplus/sigmoid Includes unit tests for parameter recovery via MLE and distribution properties. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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I ran this on sinoidal data and electricity data (test script not included in PR) and the results look reasonable. |
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pytest test/torch/modules/test_tweedie_distribution_inference.pyfrom gluonts.torch.distributions import TweedieOutput🤖 Generated with Claude Code