Compute the spatial smoother matrix for a coordinate matrix

This function computes the spatial smoother matrix for a given coordinate matrix using specified parameters.

Usage

spatial_smoother(
  coord_mat,
  sigma = 5,
  nnk = 3^(ncol(coord_mat)),
  stochastic = TRUE,
  handle_isolates = c("self_loop", "keep_zero", "drop")
)

Arguments

coord_mat

A numeric matrix representing coordinates

sigma

Numeric, the sigma parameter for the Gaussian smoother (default is 5)

nnk

Integer, the number of nearest neighbors for adjacency (default is 3^(ncol(coord_mat)))

stochastic

Logical, whether the adjacency matrix should be doubly stochastic (default is TRUE)

handle_isolates

How to treat zero-degree nodes when normalizing: "self_loop" adds a self-loop (default), "keep_zero" leaves them as zero, or "drop" removes them from the matrix.

Value

A sparse matrix representing the computed spatial smoother. If stochastic=TRUE, the matrix is row-stochastic (rows sum to 1) but not symmetric. If stochastic=FALSE, the matrix is symmetric but not row-stochastic.

Examples

coord_mat <- matrix(c(1, 2, 3, 4, 5, 6), nrow = 3, ncol = 2)

result <- spatial_smoother(coord_mat, sigma = 5, nnk = 3^(ncol(coord_mat)), stochastic = TRUE)