class statsmodels.discrete.discrete_model.NegativeBinomialP(endog, exog, p=2, offset=None, exposure=None, missing='none', **kwargs)
[source]
Generalized Negative Binomial (NB-P) model for count data
Parameters: |
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endog
array – A reference to the endogenous response variable
exog
array – A reference to the exogenous design.
p
scalar – P denotes parameterizations for NB-P regression. p=1 for NB-1 and p=2 for NB-2. Default is p=1.
cdf (X) | The cumulative distribution function of the model. | ||||
convert_params (params, mu) | |||||
cov_params_func_l1 (likelihood_model, xopt, …) | Computes cov_params on a reduced parameter space corresponding to the nonzero parameters resulting from the l1 regularized fit. | ||||
fit ([start_params, method, maxiter, …]) |
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fit_regularized ([start_params, method, …]) | Fit the model using a regularized maximum likelihood. | ||||
from_formula (formula, data[, subset, drop_cols]) | Create a Model from a formula and dataframe. | ||||
hessian (params) | Generalized Negative Binomial (NB-P) model hessian maxtrix of the log-likelihood | ||||
information (params) | Fisher information matrix of model | ||||
initialize () | Initialize is called by statsmodels.model.LikelihoodModel.__init__ and should contain any preprocessing that needs to be done for a model. | ||||
loglike (params) | Loglikelihood of Generalized Negative Binomial (NB-P) model | ||||
loglikeobs (params) | Loglikelihood for observations of Generalized Negative Binomial (NB-P) model | ||||
pdf (X) | The probability density (mass) function of the model. | ||||
predict (params[, exog, exposure, offset, which]) | Predict response variable of a model given exogenous variables. | ||||
score (params) | Generalized Negative Binomial (NB-P) model score (gradient) vector of the log-likelihood | ||||
score_obs (params) | Generalized Negative Binomial (NB-P) model score (gradient) vector of the log-likelihood for each observations. |
endog_names | Names of endogenous variables |
exog_names | Names of exogenous variables |
© 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.discrete.discrete_model.NegativeBinomialP.html