mxplot {dave} | R Documentation |
This calclulates and plots average similarities of rows (releves) in a square, classified matrix. Correlation coefficient is used as similarity, upon plotting proportionas to the surface of circles. Hence, diagonal elements exhibit similarity of groups, off-diagonals all similarities to the remaining groups.
mxplot(veg, rmember, use, y=1, ...)
matrixplot(veg, rmember, use, y=1)
## Default S3 method:
mxplot(veg, rmember, use, y=1,...)
## S3 method for class 'mxplot'
plot(x,...,capacity=100)
veg |
This is a vegetation data frame, releves are rows, species columns |
rmember |
Group membership of the rows or columns, typically taken from cluster analysis |
use |
Either "rows" or "columns" |
y |
Transformation of species scores: x'= x exp(y) |
... |
Capacity. Adjusts plot size to the number of groups. |
x |
An object of class "mxplot" |
capacity |
The number of group symbols that fit on one page |
The distance measure used is "correlation used as distance". See reference.
An object of class "mxplot" with at least the following items:
order |
Dimension of the similarity matrix (equal to the number of groups ng) |
mmatrix |
The ng x ng matrix of average group similarity |
levels |
The ng group names (a vector of character variables) |
Plot parameter capacity only affects the format of plot. Just try.
Otto Wildi
Wildi, O. 2017. Data Analysis in Vegetation Ecology. 3rd ed. CABI, Oxfordshire, Boston.
# Starts with classifying releves by cluster analysis
dd<- vegdist(sveg^0.5,method="euclid") # dd is distance matrix
o.clust<- hclust(dd,method="ward") # clustering
groups<- as.factor(cutree(o.clust,k=6)) # forming 6 groups
o.mxpl<- mxplot(sveg,groups,use="rows",y=0.5)
plot(o.mxpl,capacity=30)