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statsmodels.tools.tools.isestimable

statsmodels.tools.tools.isestimable(C, D)[source]

True if (Q, P) contrast C is estimable for (N, P) design D

From an Q x P contrast matrix C and an N x P design matrix D, checks if the contrast C is estimable by looking at the rank of vstack([C,D]) and verifying it is the same as the rank of D.

Parameters:

C : (Q, P) array-like

contrast matrix. If C has is 1 dimensional assume shape (1, P)

D: (N, P) array-like :

design matrix

Returns:

tf : bool

True if the contrast C is estimable on design D

Examples

>>> D = np.array([[1, 1, 1, 0, 0, 0],
...               [0, 0, 0, 1, 1, 1],
...               [1, 1, 1, 1, 1, 1]]).T
>>> isestimable([1, 0, 0], D)
False
>>> isestimable([1, -1, 0], D)
True

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