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statsmodels.regression.linear_model.RegressionResults.cov_params

RegressionResults.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 :

(The below are assumed to be in matrix notation.) :

cov : ndarray

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 0d :

OR :

(scale) * (X.T X)^(-1)[column][:,column] if column is 1d :

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