Data-Derived Graph Construction Utilities

Constructs data-derived graphs from numerical observations using mutual, shared-neighbor, intersection, geodesic, radius, adaptive-radius, and minimum-spanning-tree completion methods. Provides graph conversion, pruning, diagnostics, spectral embedding, endpoint detection, and path utilities. The implemented graph constructions include methods described by Jarvis and Patrick (1973) , Brito et al. (1997) , Berry and Sauer (2019) , and Gower and Ross (1969) .

dgraphs

dgraphs constructs and analyzes graphs derived from numerical observations. It includes mutual and shared-neighbor graphs, intersection and geodesic nearest-neighbor graphs, radius and adaptive-radius graphs, and minimum-spanning-tree completion. Utilities for conversion, pruning, diagnostics, spectral embedding, endpoints, and paths are also provided.

Installation

Install the released package from CRAN with:

install.packages("dgraphs")

Example

library(dgraphs)

set.seed(1)
x <- matrix(rnorm(80), ncol = 2)
graph <- create.mknn.graph(x, k = 4)

graph$n_edges

For an end-to-end introduction to graph construction, connectivity repair, parameter sequences, conversion, and diagnostics, run:

vignette("data-derived-graph-workflow", package = "dgraphs")