Detection of Edge Effects in Field Trials via Besag-Kempton Competition

Estimates and evaluates the intraspecific competition coefficient associated with the edge (border) effect in agricultural field trials, using the Besag-Kempton autoregressive model and a least-squares estimator following Darghan, Rivera, Gonzalez and Castellanos (2022) . Provides field-layout generation, spatial weight matrices, a formula interface for arbitrary two-way designs, a simulation-based decision procedure for presence or absence of the edge effect, Moran's I diagnostics, and a 'shiny' application.

BorderEffect

Detection of edge (border) effects in agricultural field trials via the Besag-Kempton competition model.

Implements the least-squares estimator of the intraspecific competition coefficient (kappa) associated with the edge effect, plus a simulation-based decision procedure, Moran's I diagnostics, and a Shiny app. Method from Darghan, Rivera, Gonzalez & Castellanos (2022), doi:10.47280/RevFacAgron(LUZ).v39.n1.18. Original research code: https://github.com/CarlosRivera1212/BorderEffect.

Installation

# install.packages("remotes")
remotes::install_github("<owner>/BorderEffect")

Quick start

library(BorderEffect)
data(field_trial)

be <- border_effect(response ~ trt + blk, data = field_trial, coords = field_trial)
bt <- border_test(be, pattern = "outer1", nsim = 500)
bt
plot(bt)

# interactive app
run_border_app()