boxplot.mvabund | R Documentation |

Draw Boxplots of `mvabund`

or `mvformula`

Objects

## S3 method for class 'mvabund' boxplot(x, y, range=1.5, names=NULL, at=NULL, n.vars=min(12,NCOL(x)), overall.main="Boxplot", var.subset=NA, transformation="log", ...) ## S3 method for class 'mvformula' boxplot( x, n.vars=12, overall.main="", var.subset=NA, ...)

`x` |
for the |

`y` |
for the |

`range` |
this determines how far the plot whiskers extend out from the box. If range is positive, the whiskers extend to the most extreme data point which is no more than range times the interquartile range from the box. A value of zero causes the whiskers to extend to the data extremes. |

`names` |
only available for the |

`at` |
only available for the |

`n.vars` |
the number of variables to include in the plot. |

`overall.main` |
a character to display as title for every window. |

`var.subset` |
a numeric vector of indices indicating which variables of the mvabund.object should be included on the plot. |

`transformation` |
an optional transformation, (ONLY) for the |

`...` |
for the For the |

The function `boxplot.mvabund`

allows simultaneous construction of many
variables on a single figure. Thus a good comparative overview about the
distribution of abundances for several species can be obtained.

There are several ways in which this function can be used.
If one `mvabund`

object, either named `x`

or `y`

or not names, is passed, it will be drawn on one plot and abundances can be
compared over several variables.

If two `mvabund`

objects, named `x`

and `y`

are
passed for plotting, they will be shown on
one plot, showing for each species the abundances of both objects directly
one below the other.

If more than two `mvabund`

objects are passed, each of them will be
plotted separately.

Additionally, it is possible to specify `x`

as a list of `mvabund`

objects.
Each of them will be plotted separately and any further `mvabund`

data will
be ignored, regardless if it is specified as `y`

or unnamed.

The function `boxplot.mvformula`

can be used to draw boxplots of a `mvabund`

object in dependence of explanatory variables. The explanatory variables can be both
numerical values as well as factor variables. If the formula contains both of them,
there will be separate plots for the terms with numerical values and the terms
with factor variables, displayed on separate windows.

The arguments `plot`

, `varwidth`

and `add`

, which are availabe in the default method of `boxplot`

, are not available for the `mvabund`

and `mvformula`

methods. The argument `horizontal`

is not available for the `mvabund`

method.

A number of other arguments like `at`

and `names`

are only available for the
`mvabund`

method.

In contrast to the default method (boxplot.default) nothing will be returned. These functions are only used for drawing the plots.

The argument `log`

, that is available in most plotting functions can not be used
for plotting `mvabund`

or `mvformula`

objects. Instead use `transformation`

for the `mvabund`

method and for the `mvformula`

method
include transformations in the formula.

Ulrike Naumann, Yi Wang, Stephen Wright and David Warton <David.Warton@unsw.edu.au>.

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

`plot.mvabund`

.

require(graphics) #### Basic Use #### data(spider) spiddat <- spider$abund X <- spider$x ## Create the mvabund object: spiddat <- mvabund(spiddat) ## Draw a boxplot for a mvabund object: boxplot(spiddat) ## the same plot could be done by plot(spiddat,type="bx") #### Advanced Use #### data(solberg) solbdat <- mvabund(solberg$abund) treatment<- solberg$x # create pch type and colour vectors treat.pch <- treat.col <- unclass(treatment) # Boxplot for data plot.mvabund(x=solbdat,y=treatment,type="bx", main="BoxPlot of The 12 Highest Abundant Species", xlab="Abundance [sqrt scale]",ylab="", transformation="sqrt",t.lab="o",shift=TRUE)

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.