plot.predict.downscale {downscale} | R Documentation |
A simple plotting function of predict.downscale
objects. Occupancy is plotted against grain size (cell area) in log-log space. Observed occupancy at large grain sizes are plotted in black, and occupancies predicted through predict.downscale
plotted in red.
## S3 method for class 'predict.downscale' plot(x, xlim = NULL, ylim = NULL, xlab = NULL, ylab = NULL, main = NULL, lwd.obs = NULL, lwd.pred = NULL, col.obs = NULL, col.pred = NULL, ...)
x |
Output object from |
xlim, ylim |
limits of axes. Defaults to minimum and maximum of data. |
xlab, ylab, main |
axis labels and title. |
lwd.obs, lwd.pred |
line width of observed and predicted occupancies ( |
col.obs, col.pred |
line and point colours of observed ( |
... |
arguments, including graphical parameters passed to other methods. |
Charles Marsh <charliem2003@gmail.com>.
See predict.downscale
and hui.downscale
for generating predict.downscale
objects.
## example species data data.file <- system.file("extdata", "atlas_data.txt", package = "downscale") atlas.data <- read.table(data.file, header = TRUE) ## upgrain data (using All Occurrences threshold) occupancy <- upgrain(atlas.data, cell.width = 10, scales = 3, method = "All_Sampled", plot = FALSE) ## Logistic model logis <- downscale(occupancies = occupancy, model = "Logis") ## predict occupancies at fine scales logis.pred <- predict(logis, new.areas = c(1, 5, 25, 100, 400, 1600, 6400)) ## plot predictions plot(logis.pred) ## change some of the plotting arguments plot(logis.pred, col.obs = "blue", pch = 16, ylim = c(0.01, 0.7))