genmod.families.family.Tweedie()
statsmodels.genmod.families.family.Tweedie
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class statsmodels.genmod.families.family.Tweedie(link=None, var_power=1.0, link_power=0)
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Tweedie family.
Parameters: link : a link instance, optional
The default link for the Tweedie family is the log link when the link_power is 0. Otherwise, the power link is default. Available links are log and Power.
var_power : float, optional
The variance power.
link_power : float, optional
The link power.
Notes
Logliklihood function not implemented because of the complexity of calculating an infinite series of summations. The variance power can be estimated using the
estimate_tweedie_power
function that is part of theGLM
class.Attributes
Tweedie.link (a link instance) The link function of the Tweedie instance Tweedie.variance (varfunc instance) variance
is an instance of statsmodels.family.varfuncs.PowerTweedie.link_power (float) The power of the link function, or 0 if its a log link. Tweedie.var_power (float) The power of the variance function. Methods
deviance
(endog, mu[, freq_weights, scale])Returns the value of the deviance function. fitted
(lin_pred)Fitted values based on linear predictors lin_pred. loglike
(endog, mu[, freq_weights, scale])The log-likelihood function 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 Tweedie family resid_dev
(endog, mu[, scale])Tweedie Deviance Residual starting_mu
(y)Starting value for mu in the IRLS algorithm. variance
alias of Power
weights
(mu)Weights for IRLS steps Methods
deviance
(endog, mu[, freq_weights, scale])Returns the value of the deviance function. fitted
(lin_pred)Fitted values based on linear predictors lin_pred. loglike
(endog, mu[, freq_weights, scale])The log-likelihood function 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 Tweedie family resid_dev
(endog, mu[, scale])Tweedie Deviance Residual 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.Tweedie.html