minmaxHelper4Partial: Computes the x- and y- axis constraints for graphs combininig...

In HerveAbdi/PTCA4CATA: Partial Triadic Analysis (PTCA) for Check All That Apply (CATA) Data

Computes the x- and y- axis constraints for graphs combininig a dataframe and a cube of partial factor sscores. Used for all prettyGraphs and prettyGraph-like (e.d. PTCA4CATA) functions.

Description

minmaxHelper4Partial: Computes the x- and y- axis constraints for graphs combininig a dataframe and a cube of partial factor sscores. Used for all prettyGraphs and prettyGraph-like (e.d. PTCA4CATA) functions. Factors scores and partial factor scores should be describing the same set of I observations.

Usage

minmaxHelper4Partial(
  FactorScores,
  partialFactorScores,
  axis1 = 1,
  axis2 = 2,
  expansionFactor = 1.1
)

Arguments

FactorScores	An I observations by J dimensions data frame od factor scores
partialFactorScores	An I observations by J dimensions by K block array of partial factor scores.
axis1	(Default: 1) the number of the first dimension of interest.
axis2	(Default: 2) the number of the second dimension of interest.
expansionFactor	(Default: 1.1) a multiplicative factor for the list (when larger than 1 this is an expansion, smaller than 1 this is a shrinkage).

Value

A list with minx, miny, maxx, maxy that can be used by various graphic functions from, for example, prettyGraphs, DistatisR, or PTCA4CATA.

Author(s)

Herve Abdi & Derek Beaton

Examples

## Not run: 
testminmax <- minmaxHelper4Partial(someScores, somePartialScores )

## End(Not run)

HerveAbdi/PTCA4CATA documentation built on July 17, 2022, 5:41 a.m.