functional_distances: Compute pairwise functional distances and cluster curves

In r4pde: Tools for Quantitative Plant Disease Epidemiology

Compute pairwise functional distances and cluster curves

Description

Computes L2 functional distances among treatment mean trajectories evaluated on a common time grid from a functional_curves object. Also computes curve-level distances, performs hierarchical clustering, and optionally performs permutation testing.

Usage

functional_distances(
  object,
  cluster_k = 4,
  hc_method = "ward.D2",
  test_factor = NULL,
  n_perm = 999,
  test_mode = c("auto", "none", "global", "global_pairwise"),
  min_strata_for_pairwise = 6,
  perm_unit = NULL,
  perm_strata = NULL,
  bootstrap = FALSE,
  boot_B = 399,
  boot_seed = 1,
  boot_ci = c(0.025, 0.975),
  show_progress = TRUE,
  curve_level = NULL,
  ...
)

Arguments

object	An object of class functional_curves.
cluster_k	Number of clusters used to cut the hierarchical tree.
hc_method	Clustering linkage method passed to stats::hclust().
test_factor	Optional a priori grouping used for a distance-based permutation test.
n_perm	Number of permutations for the distance-based test.
test_mode	Character; permutation test mode.
min_strata_for_pairwise	Minimum number of strata levels required for pairwise tests.
perm_unit	Optional character naming the unit at which group labels are permuted.
perm_strata	Optional character naming a factor defining restricted permutation strata.
bootstrap	Logical; if TRUE, compute bootstrap envelopes and distance summaries.
boot_B	Integer number of bootstrap replicates.
boot_seed	Integer seed for bootstrap resampling.
boot_ci	Length-2 numeric vector of quantiles for bootstrap intervals.
show_progress	Logical; whether to show progress.
curve_level	Logical; whether to compute curve-level distance matrix.
...	Additional arguments.

Value

An object of class "functional_distances" containing:

• distance: treatment-by-treatment functional distance matrix;

• distance_table: pairwise distances as a data frame;

• hc: hclust object;

• clusters: treatment cluster assignments;

• curve_distance: curve-by-curve distance matrix;

• test: permutation test results;

• bootstrap: bootstrap results if requested.

Examples

## Not run: 
fd <- functional_distances(fc, cluster_k = 4)
print(fd)
plot_dendrogram(fd)
plot_curves(fd)

## End(Not run)

r4pde documentation built on Sept. 8, 2026, 1:10 a.m.