plot.gdm: Plot Model Fit and I-splines from a Fitted Generalized Dissimilarity Model.

Description

plot is used to plot the I-splines and fit of a generalized dissimilarity model created using the gdm function.

Usage

# S3 method for gdm
plot(x, plot.layout = c(2, 2), plot.color = "blue",
  plot.linewidth = 2, include.rug = FALSE, rug.sitepair = NULL, ...)

Value

plot returns NULL. Use summary.gdm to obtain a synopsis of the model object.

Arguments

x: A gdm model object returned from gdm.
plot.layout: This argument specifies the row and column layout for the plots, including: (1) a single page plot of observed response data against the raw linear predictor (ecological distance) from the model, and (2) a single page plot of the observed response against the predicted response from the model, i.e. after applying the link function, 1.0 - exp(-y), to the linear predictor, and (3) the I-splines fitted to the individual predictors. Default is 2 rows by 2 columns. To produce one predictor plot per page set plot.layout to c(1,1). The first two model plots are always produced on a single page each and therefore the layout parameter affects only the layout of the I-spline plots for those predictors that featured in the model fitting process (i.e., predictors with all-zero I-spline coefficients are not plotted).
plot.color: Color of the data points that are plotted for the overall plots.
plot.linewidth: The line width for the regression line over-plotted in the two overall plots to optimize the display of the line over the data points.
include.rug: Whether or not to include a rug plot of the predictor values used to fit the gdm in the I-spline plots. When set to TRUE, a s ite-pair table must be supplied for the rug.sitepair argument. Default is FALSE.
rug.sitepair: A site-pair table used to add a rug plot of the predictor values used to fit the gdm in the I-spline plots. This should be the same site-pair table used to fit the gdm model being plotted. The function does not check whether the supplied site-pair table matches that used in model fitting.
...: Ignored.

References

Ferrier S, Manion G, Elith J, Richardson, K (2007) Using generalized dissimilarity modelling to analyse and predict patterns of beta diversity in regional biodiversity assessment. Diversity & Distributions 13:252-264.

Examples

Run this code

##set up site-pair table using the southwest data set
sppData <- southwest[c(1,2,13,14)]
envTab <- southwest[c(2:ncol(southwest))]
sitePairTab <- formatsitepair(sppData, 2, XColumn="Long", YColumn="Lat",
                              sppColumn="species", siteColumn="site",
                              predData=envTab)

##create GDM
gdmMod <- gdm(sitePairTab, geo=TRUE)

##plot GDM
plot(gdmMod, plot.layout=c(3,3))