This node constructs a contiguity spatial weights matrix from the input data.
The name of the geometry column in the input data.
Select the column which contains for each observation in the input data a unique ID, it should be an integer column. If 'none' is selected, the IDs will be automatically generated from 0 to the number of rows flowing the order of the input data. The IDs of this column must match with the values of the ID column selected in subsequent ESDA or spatial modeling nodes.
The type of spatial weights to construct. Defaults to 'Queen'. Other options are 'Rook', 'Binary Distance Band', 'Inverse Distance', 'Lattice', 'K nearest', 'Kernel', and 'Get spatial weights matrix from file'.
Queen which will construct a queen contiguity weights matrix, is more robust and more suitable for areal unit data. The queen criterion is somewhat more encompassing and defines
neighbors as spatial units sharing a common edge or a common vertex.
Rook criterion defines neighbors by the existence of a common edge between two spatial units. Therefore, the number of neighbors according to the
queen criterion will always be at least as large as for the rook criterion.
K nearest, select the nearest number 'Nearest k' in the following options. K-nearest are often used for point data.
Binary Distance Band, please select
the distance threshold 'Threshold' in the following options.
Inverse Distance, please select
the distance threshold 'Threshold' and the corresponding power 'Power' in the following options.
The order of the weight matrix is 1 by default. Users can change the order of the weights, higher order weights will treat further units as neighbors.
The distance threshold for constructing binary distance band and inverse distance weights. Defaults to 1
The number of rows for constructing a lattice spatial weights matrix. Defaults to 5.
The number of columns for constructing a lattice spatial weights matrix. Defaults to 5.
The number of nearest neighbors to use for constructing k-nearest neighbors weights. Defaults to 4.
The number of nearest neighbors to use for determining the bandwidth in kernel weights. Defaults to 12.
The type of kernel to use in constructing kernel weights. Defaults to 'triangular'
The type of kernel bandwidth to use in constructing kernel weights. The bandwidth of the kernel. The default is fixed. If adaptive then bandwidth is adaptive across observations.
The file path of a user-defined spatial weights matrix in CSV format. Defaults to ''. Please enter the path of the spatial weights matrix in CSV format in the following options. The weights matrix must be in matrix format and in the order of the samples.
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