pip {nexus} | R Documentation |
Proportionality Index of Parts (PIP)
Description
Computes an index of association between parts.
Usage
pip(x, ...)
## S4 method for signature 'CompositionMatrix'
pip(x)
Arguments
x |
A |
... |
Currently not used. |
Details
The proportionality index of parts (PIP) is based on the
variation matrix, but maintains the range of values whithin
(0,1)
.
Value
A matrix
.
Author(s)
N. Frerebeau
References
Egozcue, J. J.. & Pawlowsky-Glahn, V. (2023). Subcompositional Coherence and and a Novel Proportionality Index of Parts. SORT, 47(2): 229-244. doi:10.57645/20.8080.02.7.
See Also
Other statistics:
aggregate()
,
condense()
,
covariance()
,
dist
,
mahalanobis()
,
margin()
,
mean()
,
quantile()
,
scale()
,
variance()
,
variance_total()
,
variation()
Examples
## Data from Aitchison 1986
data("hongite")
## Coerce to compositional data
coda <- as_composition(hongite)
## Variation matrix
## (Aitchison 1986, definition 4.4)
(varia <- variation(coda))
## Cluster dendrogram
d <- as.dist(varia)
h <- hclust(d, method = "ward.D2")
plot(h)
## Heatmap
stats::heatmap(
varia,
distfun = stats::as.dist,
hclustfun = function(x) stats::hclust(x, method = "ward.D2"),
symm = TRUE,
scale = "none"
)
[Package nexus version 0.6.0 Index]