Produces an histogram of univariate ILR data (see Filzmoser et al., 2009).
methods
## S4 method for signature 'CompositionMatrix'hist( x,..., select =1, breaks ="Sturges", freq =FALSE, labels =FALSE, main =NULL, sub =NULL, ann = graphics::par("ann"), axes =TRUE, frame.plot = axes
)
Arguments
x: A CompositionMatrix object.
...: Further graphical parameters.
select: A length-one vector of column indices.
breaks: An object specifying how to compute the breakpoints (see graphics::hist()).
freq: A logical scalar: should absolute frequencies (counts) be displayed? If FALSE (the default), relative frequencies (probabilities) are displayed (see graphics::hist()).
labels: A logical scalar: should labels be drawn on top of bars? If TRUE, draw the counts or rounded densities; if labels is a character vector, draw itself.
main: A character string giving a main title for the plot.
sub: A character string giving a subtitle for the plot.
ann: A logical scalar: should the default annotation (title and x and y axis labels) appear on the plot?
axes: A logical scalar: should axes be drawn on the plot?
frame.plot: A logical scalar: should a box be drawn around the plot?
Returns
hist() is called for its side-effects: is results in a graphic being displayed (invisibly return x).
Examples
## Data from Aitchison 1986data("hongite")## Coerce to compositional datacoda <- as_composition(hongite)## Boxplot plothist(coda, select ="A")hist(coda, select ="B")
References
Filzmoser, P., Hron, K. & Reimann, C. (2009). Univariate Statistical Analysis of Environmental (Compositional) Data: Problems and Possibilities. Science of The Total Environment, 407(23): 6100-6108. tools:::Rd_expr_doi("10.1016/j.scitotenv.2009.08.008") .
See Also
Other plot methods: as_graph(), barplot(), pairs(), plot()