internal use. \(W_{ij} = | A_i \, cap \, B_j |\).
w_col(source_unit, target)build_w(source, target)
est_w(W, source_dt, target)
var_w(W, var_vec, target, method = "CS", rho_mi)
A \(n \times m\)
numeric matrix. Where \(n\) is the
number of observations in the target and \(m\) is the sample size in
the source dataset.
a single geometry from the source dataset.
a sf object - target spatial data.
a sf object - source spatial data.
the weight matrix.
a data.frame object representing the source dataset
but excluding the geometry, i.e. the spatial information,
column.
a numeric vector with variances observed at the source
data.
a character representing the method to approximate the
variance of the AI estimates. Possible values are "CS"
(Cauchy-Schwartz) or "MI" (Moran's I).
numeric calculated Moran's I.