InverseGaussian.loglike()

statsmodels.genmod.families.family.InverseGaussian.loglike

InverseGaussian.loglike(endog, mu, freq_weights=1.0, scale=1.0) [source]

The log-likelihood function in terms of the fitted mean response.

Parameters:

Parameters:	endog : array-like Endogenous response variable mu : array-like Fitted mean response variable freq_weights : array-like 1d array of frequency weights. The default is 1. scale : float, optional The default is 1.
Returns:	llf : float The value of the loglikelihood function evaluated at (endog,mu,freq_weights,scale) as defined below.

endog : array-like

Endogenous response variable

mu : array-like

Fitted mean response variable

freq_weights : array-like

1d array of frequency weights. The default is 1.

scale : float, optional

The default is 1.

Returns:

llf : float

The value of the loglikelihood function evaluated at (endog,mu,freq_weights,scale) as defined below.

$llf = -1/2 * \sum_i freq\_weights_i * ((Y_i - \mu_i)^2 / (Y_i * \mu_i * scale) + \log(scale * Y_i^3) + \log(2 * \pi))$

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© 2006–2008 Scipy Developers
© 2006 Jonathan E. Taylor
Licensed under the 3-clause BSD License.
http://www.statsmodels.org/stable/generated/statsmodels.genmod.families.family.InverseGaussian.loglike.html