statsmodels.genmod.families.family.Binomial¶
-
class
statsmodels.genmod.families.family.
Binomial
(link=None)[source]¶ Binomial exponential family distribution.
- Parameters
- link
a
link
instance
,optional
The default link for the Binomial family is the logit link. Available links are logit, probit, cauchy, log, and cloglog. See statsmodels.genmod.families.links for more information.
- link
See also
statsmodels.genmod.families.family.Family
Parent class for all links.
- Link Functions
Further details on links.
Notes
endog for Binomial can be specified in one of three ways: A 1d array of 0 or 1 values, indicating failure or success respectively. A 2d array, with two columns. The first column represents the success count and the second column represents the failure count. A 1d array of proportions, indicating the proportion of successes, with parameter var_weights containing the number of trials for each row.
- Attributes
- Binomial.link
a
link
instance
The link function of the Binomial instance
- Binomial.variance
varfunc
instance
variance
is an instance of statsmodels.genmod.families.varfuncs.binary
- Binomial.link
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.
initialize
(endog, freq_weights)Initialize the response variable.
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 Binomial 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)The starting values for the IRLS algorithm for the Binomial family.
weights
(mu)Weights for IRLS steps
Properties
Link function for family