GLS.loglike()

statsmodels.regression.linear_model.GLS.loglike

GLS.loglike(params) [source]

Returns the value of the Gaussian log-likelihood function at params.

Given the whitened design matrix, the log-likelihood is evaluated at the parameter vector params for the dependent variable endog.

Parameters:

Parameters:	params : array-like The parameter estimates
Returns:	loglike : float The value of the log-likelihood function for a GLS Model.

params : array-like

The parameter estimates

Returns:

loglike : float

The value of the log-likelihood function for a GLS Model.

Notes

The log-likelihood function for the normal distribution is

$-\frac{n}{2}\log\left(\left(Y-\hat{Y}\right)^{\prime}\left(Y-\hat{Y}\right)\right)-\frac{n}{2}\left(1+\log\left(\frac{2\pi}{n}\right)\right)-\frac{1}{2}\log\left(\left|\Sigma\right|\right)$

Y and Y-hat are whitened.

Links:

http://statsmodels.sourceforge.net/stable/generated/statsmodels.regression.linear_model.GLS.loglike.html

doc_statsmodels

2017-01-18 16:09:49

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