oraclesai.regression.SpatialRegimesRegressor

class SpatialRegimesRegressor(spatial_weights_definition=None)

The regression equation parameters are estimated according to a categorical variable called regime; this categorical variable can represent different things, such as a region in a spatial context. Neighborhoods, such as district or block names, can be used to define regimes. The model consists of linear regression models where the terms of the linear equation vary depending on the regime.

Parameters:

spatial_weights_definition – SpatialWeightsDefinition, default=None. Specifies the spatial relationship among neighbors.

Methods

__init__([spatial_weights_definition])
fit(X, y[, geometries, crs, ...])	The parameter regimes indicates the categorical variable used as regime.
get_params([deep])	Get parameters for this estimator.
predict(X[, regimes, geometries, ...])	Evaluates the model using the given data and the regimes.
score(X, y[, sample_weight, regimes, ...])	Returns R-Squared metric.
set_params(**params)	Set the parameters of this estimator.

Attributes

betas	returns: An array with the estimated parameters of the trained model
diagnostics	returns: A SpatialDiagnostics instance containing statistics of the trained model. If no
k	returns: The number of variables for which coefficients are estimated (including the
model_type	returns: The regression model defined
predy	returns: An array with the predictions for the training data
summary	returns: The summary of the trained model
u	returns: An array with the residuals of the trained model