GLM - GLM Model Definition

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

Syntax

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 Gaussian (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).

Value	Lvk
1	Identity (Residuals ~ Normal distribution) (default).
2	Log (Residuals ~ Poisson distribution).
3	Logit (Residuals ~ Binomial distribution).
4	Probit (Residuals ~ Binomial distribution).
5	Complementary log-log (Residuals ~ Binomial distribution).

Remarks

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

Files Examples

Related Links

• Wikipedia - Generalized linear model.

References

• Hamilton, J.D.; Time Series Analysis, Princeton University Press (1994), ISBN 0-691-04289-6.
• Tsay, Ruey S.; Analysis of Financial Time Series John Wiley & SONS. (2005), ISBN 0-471-690740.