pip: Proportionality Index of Parts (PIP)

In nexus: Sourcing Archaeological Materials by Chemical Composition

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 CompositionMatrix object.
...	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. \Sexpr[results=rd]{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"
)

nexus documentation built on Sept. 11, 2024, 6:43 p.m.