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.