Logit.pdf()

statsmodels.discrete.discrete_model.Logit.pdf

Logit.pdf(X) [source]

The logistic probability density function

Parameters:

Parameters:	X : array-like `X` is the linear predictor of the logit model. See notes.
Returns:	pdf : ndarray The value of the Logit probability mass function, PMF, for each point of X. `np.exp(-x)/(1+np.exp(-X))**2`

X : array-like

X is the linear predictor of the logit model. See notes.

Returns:

pdf : ndarray

The value of the Logit probability mass function, PMF, for each point of X. np.exp(-x)/(1+np.exp(-X))**2

In the logit model,

$\lambda\left(x^{\prime}\beta\right)=\frac{e^{-x^{\prime}\beta}}{\left(1+e^{-x^{\prime}\beta}\right)^{2}}$

© 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.pdf.html