# GLM_GUESS - Initial Values of GLM Model's Parameters

Returns an array of cells for the initial (non-optimal) guess of the model's parameters.

## Syntax

GLM_GUESS(Y, X, Phi, Lvk)
Y
is the response or the dependent variable data array (one dimensional array of cells (e.g. rows or columns)).
X
is the independent variables data matrix, such that each column represents one variable.
Phi
is the GLM dispersion paramter. Phi is only meaningful for Binomial (1/batch or trial size) and for Guassian (variance).
Distribution PHI
Gaussian Variance
Poisson 1.0
Binomial Reciprocal of the batch/trial size)
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).
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)

## Remarks

1. The underlying model is described here.
2. GLM_GUESS returns an array of size equal number of betas plus one (Phi).
3. The number of rows in response variable (Y) must be equal to number of rows of the explanatory variables (X).
4. For GLM with Poisson distribution,
• The values of response variable must be non-negative integers.
• The value of the dispersion factor (Phi) must be either missing or equal to one.
5. For GLM with Binomial distribution,
• The values of the response varaible must be non-negative fractions between zero and one, inclusive.
• The value of the dispersion factor (Phi) must be a positive fraction (greater than zero, and less than one).
6. For GLM with Guassian distribution, the dispersion factor (Phi) value must be either missing or positive.