Probit.jac()

statsmodels.discrete.discrete_model.Probit.jac

Probit.jac(*args, **kwds)

jac is deprecated, use score_obs instead! Use score_obs method. jac will be removed in 0.7

Probit model Jacobian for each observation

Parameters:

Parameters:	params : array-like The parameters of the model
Returns:	jac : ndarray, (nobs, k_vars) The derivative of the loglikelihood for each observation evaluated at `params`.

params : array-like

The parameters of the model

Returns:

jac : ndarray, (nobs, k_vars)

The derivative of the loglikelihood for each observation evaluated at params.

Notes

$\frac{\partial\ln L_{i}}{\partial\beta}=\left[\frac{q_{i}\phi\left(q_{i}x_{i}^{\prime}\beta\right)}{\Phi\left(q_{i}x_{i}^{\prime}\beta\right)}\right]x_{i}$

for observations $i=1,...,n$

Where $q=2y-1$ . This simplification comes from the fact that the normal distribution is symmetric.

Links:

http://statsmodels.sourceforge.net/stable/generated/statsmodels.discrete.discrete_model.Probit.jac.html

doc_statsmodels

2017-01-18 16:14:21

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