This node is currently not available in KNIME v5.3 — instead we’re showing this page for **KNIME v5.1**. You can use the version menu in the title bar to permanently switch your preferred version. This will also show the link to the update site.

Spatial two stage least squares (S2SLS) with results and diagnostics. More details can be found in the following reference, 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.

- 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 Spatial 2SlS.

- Independent variables
The columns containing the independent variables to use for the calculation of Spatial 2SlS.

- Orders of W
Orders of W to include as instruments for the spatially lagged dependent variable. For example, w_lags=1, then instruments are WX; if w_lags=2, then WX, WWX; and so on.

- Spatial Diagnostics
If selected, the node computes the Anselin-Kelejian test

- Robust
If ‘white’, then a White consistent estimator of the variance-covariance matrix is given. If ‘hac’, then a HAC consistent estimator of the variance-covariance matrix is given. Set to None for default.

- 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 Spatial 2SlS.

- Independent variables
The columns containing the independent variables to use for the calculation of Spatial 2SlS.

- Orders of W
Orders of W to include as instruments for the spatially lagged dependent variable. For example, w_lags=1, then instruments are WX; if w_lags=2, then WX, WWX; and so on.

- Spatial Diagnostics
If selected, the node computes the Anselin-Kelejian test.

- Robust
If ‘white’, then a White consistent estimator of the variance-covariance matrix is given. If ‘hac’, then a HAC consistent estimator of the variance-covariance matrix is given. Set to None for default.

- Sig2n k
If True, then use n-k to estimate sigma^2. If False, use n. Default set to True.

Advanced Setting

- VM
If True, include variance-covariance matrix in summary results. Default set to False.

- Model Summary View
- Model Summary View of Spatial 2SlS

- No workflows found

- No links available

You want to see the source code for this node? Click the following button and we’ll use our super-powers to find it for you.

To use this node in KNIME, install the extension Geospatial Analytics Extension for KNIME from the below update site following our NodePit Product and Node Installation Guide:

v5.1

A zipped version of the software site can be downloaded here.

Deploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud
or on-premises – with our brand new **NodePit Runner**.

Do you have feedback, questions, comments about NodePit, want to support this platform, or want your own nodes or workflows listed here as well? Do you think, the search results could be improved or something is missing? Then please get in touch! Alternatively, you can send us an email to mail@nodepit.com, follow @NodePit on Twitter or botsin.space/@nodepit on Mastodon.

**Please note that this is only about NodePit. We do not provide general support for KNIME — please use the KNIME forums instead.**