| Weight-class | R Documentation |
A wrapper class for p_GeoDaWeight class
gda_wAn object of p_GeoDaWeight-class
is_symmetricIf weights matrix is symmetric
sparsitySparsity of weights matrix
min_neighborsMinimum number of neighbors
max_neighborsMaximum number of neighbors
num_obsNumber of observations
mean_neighborsMean number of neighbors
median_neighborsMedian number of neighbors
has_isolatesIf the weights matrix has any isolates
GetNeighborWeights(idx)Get weights values of neighbors for idx-th observation, idx starts from 0
GetNeighbors(idx)Get neighbors for idx-th observation, idx starts from 0
GetPointer()Get the C++ object pointer (internally used)
GetSparsity()Get sparsity computed from weights matrix
HasIsolates()Check if weights matrix has isolates, or if any observation has no neighbors
IsSymmetric()Check if weights matrix is symmetric
SaveToFile(out_path, layer_name, id_name, id_values)Save current spatial weights to a file.
out_path: The path of an output weights file
layer_name : The name of the layer of input dataset
id_name : The id name (or field name), which is an associated column
contains unique values, that makes sure that the weights are connected
to the correct observations in the data table.
id_values : The tuple of values of selected id_name (column/field)
SetNeighbors(idx, nbrs)Set neighbors for one observation
SetNeighborsAndWeights(idx, nbrs, nbr_w)Set neighbors with weights values for one observation
SpatialLag(values)Compute spatial lag values for values of selected variable
Update(updateStats = TRUE)Update the weights meta data
initialize(o_gda_w)Constructor with a GeoDaWeight object (internally used)
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