Title: An Introduction to Applied Multivariate Analysis with R
Date: 2025-01-29
Version: 1.0-9
Description: Functions, data sets, analyses and examples from the book ‘An Introduction to Applied Multivariate Analysis with R’ (Brian S. Everitt and Torsten Hothorn, Springer, 2011).
Depends: HSAUR2
Suggests: mvtnorm, mclust, lattice, flexclust, nlme, RLRsim, multcomp, ape, MASS, sem, KernSmooth, scatterplot3d, ellipse
URL: http://dx.doi.org/10.1007/978-1-4419-9650-3
License: GPL-2
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2025-01-29 11:52:59 UTC; hothorn
Author: Brian S. Everitt [aut], Torsten Hothorn ORCID iD [aut, cre]
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>
Repository: CRAN
Date/Publication: 2025-01-29 12:20:02 UTC

Bivariate Boxplot

Description

Boxplots in two dimensions

Usage

bvbox(a, d = 7, mtitle = "Bivariate Boxplot", method = "robust", 
      xlab = "X", ylab = "Y", add = FALSE, ...)

Arguments

a

a matrix

d

dimension

mtitle

title

method

character

xlab

x axis label

ylab

y axis label

add

add to existing plot?

...

additional plot arguments

Details

See Chapter 2: Visualization.


Chi-squared Plot

Description

Chi-squared plot for independence

Usage

chiplot(x, y, ...)

Arguments

x

a numeric vector

y

a numeric vector

...

additional plot arguments

Details

See Chapter 2: Visualization.


Stalactite plot

Description

The stalactite plot, specifically designed for the detection and identification of multivariate outliers.

Usage

stalac(x)

Arguments

x

numeric vector

Details

See Chapter 2: Visualization.