eHOF (version 1.16)

plot.HOF: Plot Hierarchical Logistic Regression Models

Description

Plot single or multiple HOF models with or without model parameters.

Usage

# S3 method for HOF
plot(
  x,
  marginal = c("bar", "rug", "hist", "points", "n"),
  boxp = TRUE,
  las.h = 1,
  yl,
  main,
  model,
  test = "AICc",
  modeltypes,
  onlybest = TRUE,
  penal,
  gam = FALSE,
  selectMethod,
  silent = FALSE,
  para = FALSE,
  gam.se = FALSE,
  color,
  newdata = NULL,
  lwd = 1,
  leg = TRUE,
  add = FALSE,
  xlabel,
  ...
)

Arguments

x

an object from HOF(spec, ...).

marginal

type of marginal representation for occurrences/absences.

boxp

plotting of horizontal boxplots

las.h

orientation of axes labels (0 = vertical, 1 = horizontal)

yl

range of y axis, useful for rare species. Must be given as fraction of M (between 0 and 1).

main

optional plot title

model

specific HOF model used, if not selected automatically.

test

See pick.model

modeltypes

vector of suggested model types

onlybest

plot only the best model according to chosen Information criterion. If set to FALSE all calculated models will be plotted, but the best model with a thicker line.

penal

penalty term for model types, default is the number of model parameter

gam

plot Generalized additive response

selectMethod

See pick.model

silent

Print messages

para

should model parameters (optima, raw.mean, niche,..) be plotted.

gam.se

plotting of two times standard error of predict.gam as confidence interval

color

model line color, vector of length seven

newdata

curves are plotted for original x-values. Otherwise you have to provide a vector with new gradient values.

lwd

line width of model curve(s)

leg

legend for model type (and parameters)

add

add to existing plot

xlabel

x axis label

...

further arguments passed to or from other methods.

Author

Florian Jansen

Details

Plottype layout will give a normal plot for a single species, or if the HOF object contains several species, the graphics display will be divided by autolayout. Multiple species can also be plotted by a lattice xyplot and plotted with plot.HOF for every species. The third option (plottype='all') plots all selected species on the same graph which might be useful to evaluate e.g. the species within one vegetation plot, see examples.

A rug adds a rug representation (1-d plot) of the data to the plot. A rug plot is a compact way of illustrating the marginal distributions of x. Positions of the data points along x and y are denoted by tick marks, reminiscent of the tassels on a rug. Rug marks are overlaid onto the axis. A dit='bar' plot will display the original response values. For binary data this will be identical to rug.

References

de la Cruz Rot M (2005) Improving the Presentation of Results of Logistic Regression with R. Bulletin of the Ecological Society of America 86: 41-48

See Also

[HOF()]

Examples

  data(acre)
  sel <- c('MATRREC', 'RUMEACT', 'SILENOC', 'APHAARV', 'MYOSARV', 'DESUSOP', 'ARTE#VU')
  mo <- HOF(acre[match(sel, names(acre))], acre.env$PH_KCL, M=1, bootstrap=NULL)
  par(mar=c(2,2,1,.1))
  plot(mo, para=TRUE)

  #' An example for plottype='all' to show species responses for the species within
  #' the most acidic and the most calcareous vegetation plot.
  if (FALSE) {
    allSpeciesFromAnAcidicPlot <- acre['57',] > 0
    mods.acidic <- HOF(acre[,allSpeciesFromAnAcidicPlot],acre.env$PH_KCL,M=1,bootstrap=NULL)
    allSpeciesFromAnCalcareousPlot <- acre['87',] > 0
    mods.calc <- HOF(acre[,allSpeciesFromAnCalcareousPlot],acre.env$PH_KCL,M=1,bootstrap=NULL)

    autolayout(2)
    plot(mods.acidic, plottype='all', main='Plot with low pH')
    abline(v=acre.env$PH_KCL[acre.env$RELEVE_NR == '57'])
    names(mods.acidic)

    plot(mods.calc, plottype='all', main='Plot with high pH')
    abline(v=acre.env$PH_KCL[acre.env$RELEVE_NR == '87'])
    names(mods.calc)
  }