WLS.loglike()

statsmodels.regression.linear_model.WLS.loglike

WLS.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 Y.

Parameters:

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

params : array-like

The parameter estimates.

Returns:

llf : float

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

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

where $W$ is a diagonal matrix

© 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.regression.linear_model.WLS.loglike.html