Provides functions to estimate the size-controlled phenotypic integration index, a novel method by Torices & Méndez (2014) to solve problems due to individual size when estimating integration (namely, larger individuals have larger components, which will drive a correlation between components only due to resource availability that might obscure the observed measures of integration). In addition, the package also provides the classical estimation by Wagner (1984), bootstrapping and jackknife methods to calculate confidence intervals and a significance test for both integration indices.
|Author||R. Torices, A. J. Muñoz-Pajares|
|Date of publication||2016-04-27 18:28:31|
|Maintainer||A. J. Muñoz-Pajares <firstname.lastname@example.org>|
|License||GPL (>= 2)|
cor.par: Partial correlation
paeonia: phenotypic integration example dataset #1
PHENIX-package: size-controlled phenotypic integration index
pint: Phenotypic integration index by Wagner
pint.boot: Phenotypic integration (by Wagner) bootstrap intervals
pint.jack: Phenotypic integration (by Wagner) jackknife resampling
pint.p: Phenotypic integration index (by Wagner) significance test
pintsc: size-controlled phenotypic integration
pintsc.boot: size-controlled phenotypic integration bootstrap intervals
pintsc.jack: size-controlled phenotypic integration jackknife resampling
pintsc.p: size-controlled phenotypic integration index significance...
tussilago: phenotypic integration example dataset #2
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