Scilab Function

glm - generalized linear model function with Scilab

Calling Sequence

[Result] = glm(Y,X,distribution,link_function,dispersion_parameter,constant,residual_type,maxiter,accuracy)

Parameters

Description

glm function is the main function of the glmbox Scilab package produced to analyse some of most popular statistical models belonging to wide class of the generalized linear models (GLM) such as Binomial models, Poisson models, Normal models, Gamma models and Inverse Gaussian models.

[Result] = glm(Y,X,distribution,link_function,dispersion_parameter,constant,residual_type,maxiter,accuracy) 

[Result] = glm(Y,X,distribution)

The first version of glm function provides more control for the input parameters; the second version of glm function provides a set of default parameters which are usually used for the distribution chosen

for Gamma distribution the default parameters

link_function=reciprocal_link  
dispersion_parameter='mean_deviance'
constant=1
residual_type='pearson'
maxiter=1000
accuracy=0.001

for Inverse Gaussian distribution the default parameters

link_function=power_link(-2)  
dispersion_parameter='mean_deviance'
constant=1
residual_type='pearson'
maxiter=1000
accuracy=0.001

for Normal distribution the default parameters

link_function=identity_link  
dispersion_parameter='mean_deviance'
constant=1
residual_type='pearson'
maxiter=1000
accuracy=0.001

for Poisson distribution the default parameters

link_function=logarithmic_link  
dispersion_parameter=1
constant=1
residual_type='pearson'
maxiter=1000
accuracy=0.001

for Binomial distribution the default parameters

link_function=logit_link  
dispersion_parameter=1
constant=1
residual_type='pearson'
maxiter=1000
accuracy=0.001

References:

[1] Dobson, A.J. (1990), "An Introduction to Generalized Linear Models", CRC Press.

[2] Gill, J. (2001), "Generalized Linear Models: a unified approach", (quantitative applications in the social sciences, 134). Sage Pubblications.

[3] McCullagh, P., and J.A. Nelder (1990), "Generalized Linear Models", CRC Press.

[4] Myers, R.M., Montgomery, D.C. and Vining, G.G. (2001), "Generalized Linear Models with applications in engineering and the science", John Wiley and Sons.

See Also

Author