statsmodels.discrete.discrete_model.Logit
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class statsmodels.discrete.discrete_model.Logit(endog, exog, **kwargs)
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Binary choice logit model
Parameters: - endog (array-like) – 1-d endogenous response variable. The dependent variable.
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exog (array-like) – A nobs x k array where
nobs
is the number of observations andk
is the number of regressors. An intercept is not included by default and should be added by the user. Seestatsmodels.tools.add_constant
. - missing (str) – Available options are ‘none’, ‘drop’, and ‘raise’. If ‘none’, no nan checking is done. If ‘drop’, any observations with nans are dropped. If ‘raise’, an error is raised. Default is ‘none.’
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endog
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array – A reference to the endogenous response variable
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exog
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array – A reference to the exogenous design.
Methods
cdf
(X)The logistic cumulative distribution function 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, …])Fit the model using maximum likelihood. 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)Logit model Hessian matrix 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)Log-likelihood of logit model. loglikeobs
(params)Log-likelihood of logit model for each observation. pdf
(X)The logistic probability density function predict
(params[, exog, linear])Predict response variable of a model given exogenous variables. score
(params)Logit model score (gradient) vector of the log-likelihood score_obs
(params)Logit model Jacobian of the log-likelihood for each observation Attributes
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.Logit.html