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Histogram of Compositional Data

Source: R/AllGenerics.R, R/hist.R
hist.Rd

Produces an histogram of univariate ILR data (see Filzmoser et al., 2009).

Usage

# S4 method for class 'CompositionMatrix'
hist(
  x,
  ...,
  freq = FALSE,
  ncol = NULL,
  flip = FALSE,
  main = NULL,
  sub = NULL,
  ann = graphics::par("ann"),
  axes = TRUE,
  frame.plot = axes
)

Arguments

x

A CompositionMatrix object.

...

Further parameters to be passed to graphics::hist().

freq

A logical scalar: should absolute frequencies (counts) be displayed? If FALSE (the default), relative frequencies (probabilities) are displayed (see graphics::hist()).

ncol

An integer specifying the number of columns to use. Defaults to 1 for up to 4 parts, otherwise to 2.

flip

A logical scalar: should the y-axis (ticks and numbering) be flipped from side 2 (left) to 4 (right) from variable to variable?

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?

Value

hist() is called for its side-effects: is results in a graphic being displayed (invisibly return x).

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. doi:10.1016/j.scitotenv.2009.08.008 .

See also

Other plot methods: as_graph(), barplot(), plot(), plot_logratio

Author

N. Frerebeau

Examples

## Data from Aitchison 1986
data("hongite")

## Coerce to compositional data
coda <- as_composition(hongite)

## Boxplot plot
hist(coda)

hist(coda[, 1, drop = FALSE])


univariate_ilr(coda)
#>                A           B          C         D         E
#> H1  -0.033947644 -0.54277028 -2.2849649 -1.896978 -1.610466
#> H2  -0.050933699 -0.82284311 -1.6359869 -1.618890 -1.569527
#> H3  -0.376334118 -1.62739607 -0.4627266 -1.593860 -1.538097
#> H4   0.025458594 -0.82284311 -1.8076235 -1.545850 -1.727000
#> H5  -0.164790585 -0.33717258 -2.4826736 -1.756329 -1.840000
#> H6   0.065099767 -0.73227930 -2.2112489 -1.375966 -2.112385
#> H7  -0.153333089 -0.50076246 -2.1439635 -1.395564 -1.997417
#> H8  -0.450192668 -2.05280932 -0.2021847 -1.585674 -1.756329
#> H9  -0.251520427 -1.42916977 -0.7141050 -1.585674 -1.492939
#> H10 -0.210852206 -0.09631516 -3.5035872 -1.997417 -2.160246
#> H11 -0.002828431 -1.00256620 -1.4499355 -1.593860 -1.577563
#> H12 -0.136183892 -0.36724872 -2.5346576 -2.010907 -1.610466
#> H13 -0.510379180 -1.68027862 -0.3192712 -1.727000 -1.415581
#> H14 -0.245686949 -1.35045344 -0.8385304 -1.183120 -1.885259
#> H15 -0.107687886 -1.09643795 -1.1831204 -1.698659 -1.395564
#> H16 -0.523272418 -1.79710773 -0.2602866 -1.350453 -1.873707
#> H17 -0.193532178 -0.16192425 -3.2492404 -1.746438 -2.304557
#> H18 -0.012741007 -0.52222717 -2.4333276 -1.661511 -1.908114
#> H19 -0.219535504 -1.18312045 -0.9627112 -1.698659 -1.331758
#> H20 -0.153333089 -1.44296135 -0.8228431 -1.436040 -1.680279
#> H21 -0.119074531 -1.14144402 -1.1312778 -1.408861 -1.653430
#> H22 -0.002828431 -0.77683620 -1.8510819 -1.485629 -1.786724
#> H23 -0.039608333 -0.46901984 -2.5905293 -1.602123 -2.010907
#> H24 -0.127624554 -1.14144402 -1.0915512 -1.585674 -1.500309
#> H25 -0.116226483 -0.78061248 -1.5775634 -1.569527 -1.577563