statsmodels.genmod.families.family.Gamma

class statsmodels.genmod.families.family.Gamma(link=None)

Gamma exponential family distribution.

Parameters

linka link instance, optional

The default link for the Gamma family is the inverse link. Available links are log, identity, and inverse. See statsmodels.genmod.families.links for more information.

See also

statsmodels.genmod.families.family.Family

Parent class for all links.

Link Functions

Further details on links.

Attributes

Gamma.linka link instance

The link function of the Gamma instance

Gamma.variancevarfunc instance

variance is an instance of statsmodels.genmod.family.varfuncs.mu_squared

Methods

deviance(endog, mu[, var_weights, …])	The deviance function evaluated at (endog, mu, var_weights, freq_weights, scale) for the distribution.
fitted(lin_pred)	Fitted values based on linear predictors lin_pred.
loglike(endog, mu[, var_weights, …])	The log-likelihood function in terms of the fitted mean response.
loglike_obs(endog, mu[, var_weights, scale])	The log-likelihood function for each observation in terms of the fitted mean response for the Gamma distribution.
predict(mu)	Linear predictors based on given mu values.
resid_anscombe(endog, mu[, var_weights, scale])	The Anscombe residuals
resid_dev(endog, mu[, var_weights, scale])	The deviance residuals
starting_mu(y)	Starting value for mu in the IRLS algorithm.
variance
weights(mu)	Weights for IRLS steps

Methods

deviance(endog, mu[, var_weights, …])	The deviance function evaluated at (endog, mu, var_weights, freq_weights, scale) for the distribution.
fitted(lin_pred)	Fitted values based on linear predictors lin_pred.
loglike(endog, mu[, var_weights, …])	The log-likelihood function in terms of the fitted mean response.
loglike_obs(endog, mu[, var_weights, scale])	The log-likelihood function for each observation in terms of the fitted mean response for the Gamma distribution.
predict(mu)	Linear predictors based on given mu values.
resid_anscombe(endog, mu[, var_weights, scale])	The Anscombe residuals
resid_dev(endog, mu[, var_weights, scale])	The deviance residuals
starting_mu(y)	Starting value for mu in the IRLS algorithm.
weights(mu)	Weights for IRLS steps

Properties

link	Link function for family
links
safe_links
valid
variance