dave (version 2.0)

orank: Ranking by orthogonal components (RANK)

Description

Given a correlation matrix of rows or columns this selects the variable sharing a maximum variance with all others and declares this rank 1. Reduces the matrix (covariances, correlations) by the contribution of the variable ranked first. Repeats the process to derive consecutive ranks until no variance is left.

Usage

orank(veg, use, rlimit=5, y=1, x.axis=NULL, y.axis=NULL,...)
orank1(veg, use, rlimit=5, y=1, x.axis=NULL, y.axis=NULL)
# S3 method for default
orank(veg, use, rlimit=5, y=1, x.axis=NULL, y.axis=NULL,...)
# S3 method for orank
plot(x,...)
# S3 method for orank
summary(object,...)

Arguments

veg

This is a vegetation data frame, releves are rows, species columns

use

Either "rows" or "columns"

rlimit

The maximum number of ranks to be determined

y

Transformation of species scores: x'= x exp(y)

x.axis

Horizontal axis used for plotting result in a sampling plan

y.axis

Vertical axis used for plotting result in a sampling plan

x

An object of class "orank"

…

Further variables used for printing

object

An object of class "orank"

Value

An object of class "orank" with at least the following items:

use

Either "rows" or "columns"

n.ranks

The number of ranks

var.names

Names of the ranked variables

var.explained

Explained variance of the ranked variables

var.percent

Percentage of the variance explained

cum.var

Cummulative variance of ranked variables, percentage

x.axis

The same as input parameter x.axis

y.axis

The same as input parameter y.axis

Details

If x-axis=NULL or y-axis=NULL then a pcoa-ordination is computed and the first two axes used for plotting

References

Orloci, L. 1973. Ranking characters by a dispersion criterion. Nature 244: 371--373.

Wildi, O. 2017. Data Analysis in Vegetation Ecology. 3rd ed. CABI, Oxfordshire, Boston.

Examples

# NOT RUN {
# Uses vegetation data frame sveg with vegetation data
# and ssit with corresponding x- and y-axes scores
x.axis=ssit$x.axis ; y.axis=ssit$y.axis
o.orank<- orank(sveg,use="rows",rlimit=5,y=0.25,x.axis,y.axis)
plot(o.orank)
# }