pip function

Proportionality Index of Parts (PIP)

Proportionality Index of Parts (PIP)

Computes an index of association between parts. methods

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

Arguments

  • x: A CompositionMatrix object.
  • ...: Currently not used.

Returns

A matrix.

Details

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

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" )

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()

Author(s)

N. Frerebeau