Container that iteratively solves a spatial lag regression, y = pLag * W * y + X * B + E, over independent variables registered inside it.
| Name | Type | Description |
|---|---|---|
| P Lag | Real Value Type | Spatial autoregressive coefficient (p) used in the regression. |
| W Neighborhoods | Neighborhood Table Type | Spatial weight matrix (W) used in the regression. |
| X1 | Lookup Table Type | Values of the observed dependent variable (X1) for each region. When the observed result is not yet known, X1 stands in for it; in that case, supply a lookup table with the same number of records and every value set to zero. |
| B Coefficients | Lookup Table Type | Regression coefficients (B): the coefficient of the observed variable (index 0), followed by the coefficient of each independent variable registered in this container. |
| E Error | Real Value Type | Random error term (E) of the regression. |
None.
| Name | Type | Description | ||
|---|---|---|---|---|
| Y Result | Lookup Table Type | Result (y) of the equation y = pLag * W * y + X * B + E, solved iteratively until convergence. | ||
| Y Predicted Result | Lookup Table Type | Predicted result (y | ) of the equation y | = pLag * W * X1 + X * B + E. |
The independent variables (X) used in the regression are registered inside this container by functors representing a numbered table (Number Table), each identified by a sequential number starting at 1.
The number of coefficients supplied in B Coefficients must equal the number of independent variables registered in this container, plus one for the observed variable's own coefficient (index 0).
W represents the spatial interaction of a phenomenon: in a binary weight matrix, unit i is a neighbor of unit j when the corresponding matrix cell is 1.
References
ANSELIN, L. SpaceStat Tutorial. Urbana-Champaign, University of Illinois, 1992.
ANSELIN, L. Spatial Externalities, Spatial Multipliers and Spatial Econometrics. Urbana-Champaign, University of Illinois, 2002.
CalcSpatialLag