Stats-Regression

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• Regression inference

Namespaces

• Ordinary least squares — Lodestar.Stats.Regression — Two ways to fit a linear model by ordinary least squares.
• Weighted least squares — Lodestar.Stats.Regression — One entry point, for a linear model whose rows are not equally trusted.
• Generalized least squares — Lodestar.Stats.Regression — One entry point, for a linear model whose errors are correlated.
• Generalized linear models — Lodestar.Stats.Regression — One entry point, GeneralizedLinearModel.Fit: it fits a response through a link function instead of an identity one, by IRLS, and reports what a statsmodels GLM(...).fit() summary holds — the same inference table OrdinaryLeastSquares.Fit reports, fitted through a link instead of directly.
• Multinomial logit — Lodestar.Stats.Regression — One entry point, MultinomialLogit.Fit, for a response with more than two unordered categories.