response.plot: Analysis of the response curves of a model within Biomod

Description

Depreciated function, please use response.plot2 instead

Usage

response.plot(
  model,
  Data,
  show.variables = seq(1:ncol(Data)),
  save.file = "no",
  name = "response_curve",
  ImageSize = 480,
  plot = TRUE
)

Arguments

model: the model for which you want the response curves to be plotted. Compatible with GAM, GBM, GLM, ANN, CTA, RF, FDA and MARS.
Data: the variables for which you want the response curves to be plotted. A data frame is wanted with one column per variable. They have to have the same names as the ones used to calibrate the model.
show.variables: give in the column numbers of 'Data' for selecting the variables that are wanted for plotting
save.file: can be set to "pdf", "jpeg" or "tiff" to save the plot. Pdf options can be changed by setting the default values of pdf.options().
name: the name of the file produced if save.file is different to "no" (extensions are already included)
ImageSize: the size of the image in pixels if save.file is different to "no". Affects "jpeg" and "tiff" outputs only. Default if 480 pixels which is the R default.
plot: if TRUE (the default) then a plot is produced. If not, an array containing predictions is returned (see details)

Author

Wilfried Thuiller

Details

Depreciated function, please use response.plot2 instead.

References

Elith, J., Ferrier, S., Huettmann, FALSE. & Leathwick, J. R. 2005 The evaluation strip: A new and robust method for plotting predicted responses from species distribution models. Ecological Modelling 186, 280-289.