metalog_jax. Traditional probability distributions often fail to model real-world data. You end up trying multiple distributions, truncating to enforce bounds, using hard-to-interpret mixture models, or writing custom likelihood functions. What if one distribution family could fit virtually any continuous data?

Problem

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Audience

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Market

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Pricing

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