oraclesai.regression.SpatialFixedEffectsRegressor

class SpatialFixedEffectsRegressor(spatial_weights_definition=None)

The Spatial Fixed Effects algorithm is a simplified version of Spatial Regimes, computing an intercept or constant parameter for each regime, while the other model parameters remain constant.

Parameters:

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

Methods

__init__([spatial_weights_definition])
fit(X, y[, geometries, crs, ...])	Trains an OLS model where the intercept parameter changes depending on the regime, the rest of the parameters remain constant.
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