GLMModel: Generalized Linear Model

View source: R/ML_GLMModel.R

GLMModelR Documentation

Generalized Linear Model


Fits generalized linear models, specified by giving a symbolic description of the linear predictor and a description of the error distribution.


GLMModel(family = NULL, quasi = FALSE, ...)

  family = NULL,
  quasi = FALSE,
  direction = c("both", "backward", "forward"),
  scope = list(),
  k = 2,
  trace = FALSE,
  steps = 1000



optional error distribution and link function to be used in the model. Set automatically according to the class type of the response variable.


logical indicator for over-dispersion of binomial and Poisson families; i.e., dispersion parameters not fixed at one.


arguments passed to glm.control.


mode of stepwise search, can be one of "both" (default), "backward", or "forward".


defines the range of models examined in the stepwise search. This should be a list containing components upper and lower, both formulae.


multiple of the number of degrees of freedom used for the penalty. Only k = 2 gives the genuine AIC; k = .(log(nobs)) is sometimes referred to as BIC or SBC.


if positive, information is printed during the running of stepAIC. Larger values may give more information on the fitting process.


maximum number of steps to be considered.


GLMModel Response types:

BinomialVariate, factor, matrix, NegBinomialVariate, numeric, PoissonVariate

GLMStepAICModel Response types:

binary factor, BinomialVariate, NegBinomialVariate, numeric, PoissonVariate

Default values and further model details can be found in the source links below.

In calls to varimp for GLMModel and GLMStepAICModel, numeric argument base may be specified for the (negative) logarithmic transformation of p-values [defaul: exp(1)]. Transformed p-values are automatically scaled in the calculation of variable importance to range from 0 to 100. To obtain unscaled importance values, set scale = FALSE.


MLModel class object.

See Also

glm, glm.control, stepAIC, fit, resample


fit(sale_amount ~ ., data = ICHomes, model = GLMModel)

MachineShop documentation built on Sept. 5, 2022, 5:08 p.m.