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goglm supports estimation of generalized linear models in Go.

A basic usage example is as follows:

fam := goglm.NewFamily(goglm.BinomialFamily)
// data is a dstream
glm := goglm.NewGLM(data, "Y").Family(fam).Done()
rslt := glm.Fit()
print(rslt.Summary().String())

NewFamily returns a GLM family (here it is the Binomial family), and data is a "Dstream" as defined in the dstream package. The Dstream is used to feed data to the GLM in chunks using a column-oriented storage layout. A more extensive illustration can be found in the "examples" directory.

Supported features

• Estimation via IRLS and gonum optimizers

• Supports many GLM families, links and variance functions

• Supports estimation for case-weighted datasets

• Models can be specified using formulas

• Regularized (ridge/LASSO/elastic net) estimation

• Offsets

• Unit tests covering all families with their default links and variance functions, and some of the more common non-canonical links

Missing features

• Performance assessments

• Model diagnostics

• Less-common GLM families (e.g. Tweedie)

• Marginalization

• Missing data handling

• GEE

• Inference for survey data