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CovarianceEstimatorFunction

CovarianceEstimatorFunction
is an option for generalized linear model fitting functions that specifies the estimator for the parameter covariance matrix.

MORE INFORMATION

CovarianceEstimatorFunction is an option for GeneralizedLinearModelFit, LogitModelFit, and ProbitModelFit.

Possible settings include and which use the expected information matrix and observed information matrix, respectively.

The covariance matrix is equivalent to , where is the dispersion parameter and is Fisher's information matrix.

EXAMPLES

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Basic Examples (1)

Fit a generalized linear model:

Compute the covariance matrix using the expected information matrix:

Use the observed information matrix instead:

Fit a generalized linear model:

In[1]:=

In[2]:=

Out[2]=

Compute the covariance matrix using the expected information matrix:

In[3]:=

Out[3]=

Use the observed information matrix instead:

In[4]:=

Out[4]=

In[5]:=

Out[5]=

Scope (2)

Specify the covariance estimate within the FittedModel:

Use with LogitModelFit:

Use with ProbitModelFit:

Properties & Relations (2)

Error estimates and confidence intervals involve covariance estimates:

Estimate errors and intervals using expected information:

Use observed information:

CovarianceEstimatorFunction controls the general structure of the covariance:

DispersionEstimatorFunction affects the scale:

The ratio of the errors squared is the ratio of the dispersion estimates: