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Stats Regression
github-actions[bot] edited this page Sep 21, 2026
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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 astatsmodelsGLM(...).fit()summary holds — the same inference tableOrdinaryLeastSquares.Fitreports, 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.