statsmodels.discrete.count_model.ZeroInflatedPoissonResults.cov_params
-
ZeroInflatedPoissonResults.cov_params(r_matrix=None, column=None, scale=None, cov_p=None, other=None)
-
Returns the variance/covariance matrix.
The variance/covariance matrix can be of a linear contrast of the estimates of params or all params multiplied by scale which will usually be an estimate of sigma^2. Scale is assumed to be a scalar.
Parameters: - r_matrix (array-like) – Can be 1d, or 2d. Can be used alone or with other.
- column (array-like, optional) – Must be used on its own. Can be 0d or 1d see below.
- scale (float, optional) – Can be specified or not. Default is None, which means that the scale argument is taken from the model.
- other (array-like, optional) – Can be used when r_matrix is specified.
Returns: cov – covariance matrix of the parameter estimates or of linear combination of parameter estimates. See Notes.
Return type: ndarray
Notes
(The below are assumed to be in matrix notation.)
If no argument is specified returns the covariance matrix of a model
(scale)*(X.T X)^(-1)
If contrast is specified it pre and post-multiplies as follows
(scale) * r_matrix (X.T X)^(-1) r_matrix.T
If contrast and other are specified returns
(scale) * r_matrix (X.T X)^(-1) other.T
If column is specified returns
(scale) * (X.T X)^(-1)[column,column]
if column is 0dOR
(scale) * (X.T X)^(-1)[column][:,column]
if column is 1d
© 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.count_model.ZeroInflatedPoissonResults.cov_params.html