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The ‘predDensity’ function, included in the modEvA package since version 1.5 (currently available on R-Forge), produces a histogram and/or a kernel density plot of predicted values for observed presences and absences in a binomial GLM:

predDensity <- function (model = NULL, obs = NULL, pred = NULL, separate = TRUE, type = c("both"), legend.pos = "topright") { if (!is.null(model)) { if (!("glm" %in% class(model)) || family(model)$family != "binomial") stop("'model' must be of class 'glm' and family 'binomial'.") if (!is.null(obs)) message("Argument 'obs' ignored in favour of 'model'.") if (!is.null(pred)) message("Argument 'pred' ignored in favour of 'model'.") obs <- model$y pred <- model$fitted.values } if (is.null(obs)) { if (is.null(pred)) stop("You must provide either 'model' or 'pred'.") separate <- FALSE obs <- sample(c(0, 1), length(pred), replace = TRUE) } else { if (length(obs) != length(pred)) stop("'obs' and 'pred' must have the same length.") } pred0 <- pred[obs == 0] pred1 <- pred[obs == 1] type <- match.arg(type, c("histogram", "density", "both")) rslt <- vector("list") if (type %in% c("density", "both")) { if (!separate) { dens <- density(pred) xrange <- range(dens$x, finite = TRUE) yrange <- range(dens$y, finite = TRUE) rslt[["density"]] <- dens } else { dens0 <- density(pred0) dens1 <- density(pred1) xrange <- range(dens0$x, dens1$x, finite = TRUE) yrange <- range(dens0$y, dens1$y, finite = TRUE) rslt[["density_obs1"]] <- dens1 rslt[["density_obs0"]] <- dens0 } plot(x = xrange, y = yrange, xlab = "Predicted value", ylab = "Density", type = "n") } if (type %in% c("histogram", "both")) { hist0 <- hist(pred0, plot = FALSE) hist1 <- hist(pred1, plot = FALSE) if (type == "histogram") { yrange <- range(hist0$density, hist1$density, finite = TRUE) plot(x = c(0, 1), y = yrange, type = "n", xlab = "Predicted value", ylab = "Density") } if (!separate) { histogram <- hist(c(pred0, pred1), freq = FALSE, col = "grey20", add = TRUE) rslt[["histogram"]] <- histogram } else { hist(pred1, freq = FALSE, col = "grey20", add = TRUE) hist(pred0, freq = FALSE, col = "darkgrey", density = 40, angle = 45, add = TRUE) rslt[["histogram_obs1"]] <- hist1 rslt[["histogram_obs0"]] <- hist0 if (legend.pos != "n" && type == "histogram") legend(legend.pos, legend = c("absences", "presences"), fill = c("darkgrey", "grey20"), border = NA, density = c(40, NA), bty = "n") } } if (type %in% c("density", "both")) { if (!separate) { lines(dens, col = "black", lwd = 2) } else { lines(dens1, col = "black", lwd = 2) lines(dens0, col = "darkgrey", lty = 5, lwd = 2) if (legend.pos != "n" && type == "density") legend(legend.pos, legend = c("absences", "presences"), col = c("darkgrey", "black"), lty = c(5, 1), bty = "n") if (legend.pos != "n" && type == "both") legend(legend.pos, legend = c("absences", "presences"), fill = c("darkgrey", "grey20"), border = NA, lty = c(5, 1), col = c("darkgrey", "grey15"), density = c(40, NA), bty = "n") } } return(rslt) }

**Usage example:**

install.packages("modEvA", repos="http://R-Forge.R-project.org") library(modEvA) data(rotif.mods) predDensity(model = rotif.mods$models[[3]])

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