DispersionEstimatorFunction

is an option for generalized linear model fitting functions that specifies the estimator for the dispersion parameter.

Details

DispersionEstimatorFunction is an option for GeneralizedLinearModelFit, LogitModelFit, and ProbitModelFit.
With DispersionEstimatorFunction->"PearsonChiSquare", the estimator is where is the number of data points, is the number of parameters, and is the variance function for the distribution.
With DispersionEstimatorFunction->Automatic, the following estimates are used:
"Binomial" 1

"Gamma"

"Gaussian"

"InverseGaussian"

"Poisson" 1

"QuasiLikelihood"
Non‐default values can be used to model overdispersion in "Binomial" and "Poisson" models.
With the setting DispersionEstimatorFunction->f, the common dispersion is estimated by f[y,,w] where y={y₁,y₂,…} is the list of observations, ={,,…} is the list of predicted values, and w={w₁,w₂,…} is the list of weights for the measurements y_i.