Gaussian exponential family distribution.
Parameters: | link : a link instance, optional
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Attributes
Gaussian.link | a link instance | The link function of the Gaussian instance |
Gaussian.variance | varfunc instance | variance is an instance of statsmodels.family.varfuncs.constant |
Methods
deviance(endog, mu[, freq_weights, scale]) | Gaussian deviance function |
fitted(lin_pred) | Fitted values based on linear predictors lin_pred. |
loglike(endog, mu[, freq_weights, scale]) | The log-likelihood in terms of the fitted mean response. |
predict(mu) | Linear predictors based on given mu values. |
resid_anscombe(endog, mu) | The Anscombe residuals for the Gaussian exponential family distribution |
resid_dev(endog, mu[, scale]) | Gaussian deviance residuals |
starting_mu(y) | Starting value for mu in the IRLS algorithm. |
variance | The call method of constant returns a constant variance, i.e., a vector of ones. |
weights(mu) | Weights for IRLS steps |
Methods
deviance(endog, mu[, freq_weights, scale]) | Gaussian deviance function |
fitted(lin_pred) | Fitted values based on linear predictors lin_pred. |
loglike(endog, mu[, freq_weights, scale]) | The log-likelihood in terms of the fitted mean response. |
predict(mu) | Linear predictors based on given mu values. |
resid_anscombe(endog, mu) | The Anscombe residuals for the Gaussian exponential family distribution |
resid_dev(endog, mu[, scale]) | Gaussian deviance residuals |
starting_mu(y) | Starting value for mu in the IRLS algorithm. |
weights(mu) | Weights for IRLS steps |