Spatial Error Model

ML estimation of the spatial error model with all results and diagnostics. More details can be found at Luc Anselin. Spatial Econometrics: Methods and Models. Kluwer, Dordrecht, 1988.

Note: The input table should not contain missing values. You can use the Missing Value node to replace them.

Options

Geometry column

Select the geometry column to use.

ID column

Select the column which contains for each observation in the input data a unique ID, it should be an integer column. The IDs must match with the values of the Spatial Weights node ID column. If 'none' is selected, the IDs will be automatically generated from 0 to the number of rows flowing the order of the first input table.

Dependent variable

The column containing the dependent variable to use for the calculation of the spatial ML_Error model.

Independent variables

The columns containing the independent variables to use for the calculation of the spatial ML_Error model.

Method

if ‘full’, brute force calculation (full matrix expressions) if ‘ord’, Ord eigenvalue method if ‘LU’, LU sparse matrix decomposition

Advanced Settings

Advanced Setting

Epsilon

tolerance criterion in mimimize_scalar function and inverse_product

VM

if True, include variance-covariance matrix in summary results.

Input Ports

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Input Table with dependent and independent variables for calculation of the spatial ML_Error model.

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Input Table with spatial weights for calculation of the spatial ML_Error model.

Output Ports

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Description of the spatial ML_Error model.

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Variable and Coefficient Table of the spatial ML_Error model.

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Views

Model summary view
Model summary view of the spatial ML_Error model.

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Links

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