statsmodels.genmod.families.family.InverseGaussian¶

class statsmodels.genmod.families.family.InverseGaussian(link=None, check_link=True)[source]¶

InverseGaussian exponential family.

Parameters:¶

linka link instance, optional

The default link for the inverse Gaussian family is the inverse squared link. Available links are InverseSquared, Inverse, Log, and Identity. See statsmodels.genmod.families.links for more information.

check_linkbool

If True (default), then and exception is raised if the link is invalid for the family. If False, then the link is not checked.

Attributes:¶

InverseGaussian.linka link instance

The link function of the inverse Gaussian instance

InverseGaussian.variancevarfunc instance

variance is an instance of statsmodels.genmod.families.varfuncs.mu_cubed

Methods

variance

See also

statsmodels.genmod.families.family.Family

Parent class for all links.

Link Functions

Further details on links.

Notes

The inverse Gaussian distribution is sometimes referred to in the literature as the Wald distribution.

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.
get_distribution(mu, scale[, var_weights])	Frozen Inverse Gaussian distribution instance for given parameters
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 Inverse Gaussian 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