Proportionality Index of Parts (PIP)
Computes an index of association between parts. methods
pip(x, ...) ## S4 method for signature 'CompositionMatrix' pip(x)
x
: A CompositionMatrix
object....
: Currently not used.A matrix
.
The proportionality index of parts (PIP) is based on the variation matrix , but maintains the range of values whithin .
## 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" )
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") .
Other statistics: aggregate()
, condense()
, covariance()
, dist
, mahalanobis()
, margin()
, mean()
, quantile()
, scale()
, variance()
, variance_total()
, variation()
N. Frerebeau
Useful links