predict.spacc: Predict from Empirical Accumulation Curve

In spacc: Fast Spatial Species Accumulation Curves

Predict from Empirical Accumulation Curve

Description

Interpolate the mean empirical accumulation curve at arbitrary site counts using linear interpolation. Unlike the predict method for spacc_fit objects, this does not use a fitted model; it interpolates the observed curve directly.

Usage

## S3 method for class 'spacc'
predict(object, n = NULL, ci = TRUE, ci_level = 0.95, warn = TRUE, ...)

Arguments

object	A spacc object.
n	Numeric vector of site counts at which to interpolate. Defaults to 25%, 50%, and 100% of total sites.
ci	Logical. If TRUE (default), return a data frame with columns n, mean, lower, upper. If FALSE, return a named numeric vector.
ci_level	Confidence level for the interval (default 0.95).
warn	Logical. Warn when n values fall outside the observed range (default TRUE).
...	Ignored.

Value

A data frame (if ci = TRUE) or named numeric vector (if ci = FALSE). Out-of-range values return NA.

Examples

coords <- data.frame(x = runif(50), y = runif(50))
species <- matrix(rbinom(50 * 30, 1, 0.3), nrow = 50)
sac <- spacc(species, coords, n_seeds = 10, progress = FALSE)
predict(sac, n = c(10, 25, 50))
predict(sac, n = c(10, 25), ci = FALSE)

spacc documentation built on June 20, 2026, 5:07 p.m.