PHENIX (version 1.0)

int: Phenotypic integration index by Wagner

Description

Estimates phenotypic integration indices based on the variance of the eigenvalues of the correlatoin matrix between phenotypic traits following Wagner (1984)

Usage

int(traits)

Arguments

traits

a dataframe or a matrix object with all your traits in which columns are the traits and rows are the individuals

Value

• A list with five elements containing:
• INT:
  The phenotypic integration index.
• RelINT:
  Percentage of maximum possible integration.
• INT.c:
  Corrected phenotypic integration index.
• RelINT.c:
  Percentage of maximum possible integration.
• N:
  Number of observations used.

Details

This function allows to estimate the phenotypic integration index (INT) using the correlation matrix following Wagner (1984), as well as a phenotypic integration index (INT.c) corrected by the number of traits and individuals of each population. Both estimates are also expressed as percentage depending on the maximum possible integration levels.

References

Cheverud JM, GP Wagner, MM Dow 1989 Methods for the comparative analysis of variation patterns. Syst Zool 38:201–213

Pavlicev M, JM Cheverud, GPWagner 2009 Measuring morphological integration using eigenvalue variance. Evolutionary Biology 36: 157–170

Wagner GP 1984 On the eigenvalue distribution of genetic and phenotypic dispersion matrices: evidence for a nonrandom organization of quantitative character variation. J Math Biol 21:77–95.

See Also

intsc, int.boot

Examples

# Dataset from Torices & Méndez (2014)
# This data set represents the dry mass (in grames) of inflorescence components of the sunflower
# species Tussilago farfara. The inflorescences were dissected in 'SCAPE', 'RECEPTACLE', 'MALEFL'
# (male flowers), 'OVAR' (reproductive part of female flowers), and 'RAYS' (the petaloid ray of
# female flower). Furthermore in the last column the total weight of the inflorescence is added
# 'TOTALSIZE'

data(tussilago)
int (tussilago[,1:5]) # the last column is not included since represents the total size
# NOTE that the number of observations used by the function was 29 instead 40 that were
# included in the 'tussilago' data set. Missing values were removed.