plotMvaFactor: Draw a Mvabund Object split into groups.

In mvabund: Statistical Methods for Analysing Multivariate Abundance Data

Draw a Mvabund Object split into groups.

Description

Draw the mvabund object x but split the data into groups according to the grouping variable y.

Usage

plotMvaFactor(x, y, type="p", main="Abundance", n.vars= min(12,NCOL(x)), 
  transformation="log", legend=TRUE, ...)

Arguments

x	a mvabund object, a matrix with multivariate abundance data.
y	a factor or a data.frame with factors, non-factor columns in a data.frame are ignored.
type	what type of plot should be drawn, allowed types are "p" for scatterplot, "bx" for boxplot and "n" for no plot. Other types, as used in par are NOT allowed.
main	the title of the plot, see plot.
n.vars	the number of variables to include in the plot.
transformation	an optional transformation, "no" = untransformed, "sqrt"=square root transformed, "log" (default)=log(Y/min+1) transformed, "sqrt4" =4th root transformed.
legend	logical, whether a legend should be added to the plot.
...	arguments to be passed to or from other methods.

Details

For each variable in y that is a factor, a plot is drawn. When boxplots are drawn the colors, that can be supplied by col are used to display different factor levels. For scatterplots it is also possible to use the plotting symbols, specified by pch for that.

If the colors and for scatterplots the plotting symbols are not supplied, they will be automatically generated. However, the plotting symbols will only be automatically used in this way if there are up to seven different levels.

If colors or the plotting symbols are supplied, but the number of factor levels is bigger than the the number of different values, they will be replicated.

Sometimes the legends might be only partially visible, especially when the width of the graphics device is too small. To fix this, create a graphics device with a larger width (see help("device") for on available devices and their details) and then repeat the plotMvaFactor command.

Author(s)

Ulrike Naumann, Yi Wang, Stephen Wright and David Warton <[e-mail]>.

References

Warton, D. I. ( ) Raw data graphing: an informative but under-utilised tool for the analysis of multivariate abundances, , .

See Also

plot.mvabund.

Examples

require(graphics)

## Plot an Environment Factor vs Abundance plot
data(spider)
spiddat <- mvabund(spider$abund)

## Create a Environmental factor where TRUE=Sand, FALSE=No Sand)
X <- as.factor(spider$x$bare.sand>0)
plotMvaFactor(x=spiddat, y=X)

mvabund documentation built on March 18, 2022, 7:25 p.m.