GLM - GLM Model Definition

Returns an array of cells for the packed form of a given GLM model.



GLM(Betas, Phi, Lvk)

Betas are the coefficients of the GLM model (a one dimensional array of cells (e.g. rows or columns)).

Phi is the GLM dispersion paramter. This argument is only required for Binomial distribution (phi=1/batch size) and for Guassian (phi=sigma).

Lvk is the link function that describes how the mean depends on the linear predictor (1=Identity (default), 2=Log, 3=Logit, 4=Probit, 5=Log-Log).

Link Description
1 Identity (residuals ~ Normal distribution)
2 Log (residuals ~ Poisson distribution)
3 Logit (residuals ~ binomial distribution)
4 Probit(residuals ~ binomial distribution)
5 Complementary log-log (residuals ~ binomial distribution)


  1. The underlying model is described here.
  2. Generalized linear models were formulated by John Nelder and Robert Wedderburn as a way of unifying various other statistical models, including linear regression, logistic regression and Poisson regression, under one framework

Files Examples


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