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sklearn.gaussian_process.correlation_models.pure_nugget

sklearn.gaussian_process.correlation_models.pure_nugget(theta, d)

Spatial independence correlation model (pure nugget). (Useful when one wants to solve an ordinary least squares problem!):

                                     n
theta, dx --> r(theta, dx) = 1 if   sum |dx_i| == 0
                                   i = 1
                             0 otherwise
Parameters:

theta : array_like

None.

dx : array_like

An array with shape (n_eval, n_features) giving the componentwise distances between locations x and x’ at which the correlation model should be evaluated.

Returns:

r : array_like

An array with shape (n_eval, ) with the values of the autocorrelation model.

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