nexus (version 0.3.0)

pip: Proportionality Index of Parts (PIP)

Description

Computes an index of association between parts.

Usage

pip(x, ...)
# S4 method for CompositionMatrix
pip(x)

Value

A matrix.

Arguments

x

A CompositionMatrix object.

...

Currently not used.

Author

N. Frerebeau

Details

The proportionality index of parts (PIP) is based on the variation matrix, but maintains the range of values whithin \((0,1)\).

References

Egozcue, J. J.. & Pawlowsky-Glahn, V. (2023). Subcompositional Coherence and and a Novel Proportionality Index of Parts. SORT, 47(2): 229-244. tools:::Rd_expr_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"
)