genmod.families.family.Gaussian()
statsmodels.genmod.families.family.Gaussian
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class statsmodels.genmod.families.family.Gaussian(link=<class 'statsmodels.genmod.families.links.identity'>)
[source] -
Gaussian exponential family distribution.
Parameters: link : a link instance, optional
The default link for the Gaussian family is the identity link. Available links are log, identity, and inverse. See statsmodels.family.links for more information.
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.constantMethods
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
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
© 2009–2012 Statsmodels Developers
© 2006–2008 Scipy Developers
© 2006 Jonathan E. Taylor
Licensed under the 3-clause BSD License.
http://www.statsmodels.org/stable/generated/statsmodels.genmod.families.family.Gaussian.html