The continuous Boyce index

How consistently the predictions rise with the density of presences, without a cut and without absences (Hirzel et al. 2006). A window of width times the range of the predictions slides over that range in resolution + 1 equal steps. In each, the share of presences falling inside divided by the share of all units falling inside is the predicted-to-expected ratio, undefined where no unit falls inside, and the index is the Spearman correlation of that ratio with the window's midpoint, between -1 and 1. Predictions that rank no better than chance read near 0.

Usage

boyce_index(y, p, resolution = 100L, width = 0.1)

Arguments

y

Observed presence-absence, 0/1 or logical.

p

Predicted scores for the same units, in the same order. Higher means presence.

resolution

Number of window steps, 100 by default.

width

Window width as a share of the range of p, 0.1 by default.

Value

One number, or NA where the cell defines none, where the predictions are all equal, or where the ratio is defined in fewer than three windows or takes one value.

Details

The units of p are the background, which is how biomod2 reads BOYCE on a fit. The windows are closed at both ends and the ratio is not thinned of repeated values.

Examples

boyce_index(c(0, 0, 0, 1, 1, 1, 0, 1), c(0.10, 0.20, 0.35, 0.40, 0.60, 0.90, 0.55, 0.70))