sklearn.gaussian_process.correlation_models.pure_nugget

sklearn.gaussian_process.correlation_models.pure_nugget(theta, d)[source]

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

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

theta : array_like

None.

d : 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.