plotMvaFactor {mvabund} | R Documentation |
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 |
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 |
main |
the title of the plot, see |
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 <David.Warton@unsw.edu.au>.
References
Warton, D. I. ( ) Raw data graphing: an informative but under-utilised tool for the analysis of multivariate abundances, , .
See Also
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)