pkgdown/mathjax-config.html

Skip to contents

Predict from Empirical Accumulation Curve

Source: R/methods.R
predict.spacc.Rd

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

# \donttest{
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)
# }