moran_i: Moran's I test for spatial autocorrelation in residuals

In tulpa: Templated Unified Library for Posterior Approximation in Bayesian Hierarchical Models

Moran's I test for spatial autocorrelation in residuals

Description

Tests whether residuals exhibit spatial structure after model fitting. Supports inverse-distance and k-nearest-neighbour weight matrices. No external dependencies (uses normal approximation for inference).

Usage

moran_i(
  object,
  coords,
  weights = c("inverse", "knn"),
  k = 10L,
  resid_type = "pearson",
  alternative = c("two.sided", "greater", "less")
)

Arguments

object	A fitted model, or a numeric vector of residuals
coords	N x 2 coordinate matrix (required)
weights	Weight scheme: "inverse" or "knn"
k	Number of neighbours for knn (default 10)
resid_type	Residual type if extracting from model (default "pearson")
alternative	"two.sided", "greater", or "less"

Value

An htest object with Moran's I, expected I, and p-value

Examples

set.seed(1)
coords <- cbind(runif(50), runif(50))
resid  <- rnorm(50)
moran_i(resid, coords)

tulpa documentation built on Oct. 19, 2026, 5:09 p.m.