Binary choice Probit model
| Parameters: | endog : array-like
exog : array-like
|
|---|
Attributes
| endog | array | A reference to the endogenous response variable |
| exog | array | A reference to the exogenous design. |
| nobs | float | The number of observations of the model. |
Methods
| cdf(X) | Probit (Normal) cumulative distribution function |
| fit([start_params, maxiter, method, tol]) | Fits the binary probit model. |
| hessian(params) | Probit model Hessian matrix of the log-likelihood |
| information(params) | Fisher information matrix of model |
| initialize() | Initialize is called by |
| loglike(params) | Log-likelihood of probit model (i.e., the normal distribution). |
| pdf(X) | Probit (Normal) probability density function |
| predict(design) | After a model has been fit predict returns the fitted values. |
| score(params) | Probit model score (gradient) vector |