Returns an array of cells for the packed form of a given GLM model.
GLM(Betas, Phi, Lvk)
- are the coefficients of the GLM model (a one dimensional array of cells (e.g. rows or columns)).
- is the GLM dispersion paramter. This argument is only required for Binomial distribution (phi=1/batch size) and for Guassian (phi=sigma).
- 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)
- The underlying model is described here.
- 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