PCAbiplot: PCA of the estimated parameters

In CoDaLoMic: Compositional Models to Longitudinal Microbiome Data

PCA of the estimated parameters

Description

This function applys a PCA to the estimate parameters (using function "prcomp" with center = TRUE and scale. = TRUE). Then uses the ggbiplot function to plot the biplot.

Usage

PCAbiplot(paramEstimadosFinal, names, E)

Arguments

paramEstimadosFinal	The estimate parameters, in the following order: a11,a12,a13, a21, a22,a23, ...a(D-1)1,a(D-1)2,a(D-1)3,tau. Where D is the number of bacterial especies present in the matrix especie.
names	Vector with the name of the bacteria. The component i has the name of the bacteria i, with i=1,...,D. The bacteria in the las position of the vector is the bacteria used as reference in the alr transformation.
E	Number of bacteria available.

Value

Returns a list with the PCA biplot, the variance explained of each Principal Component and an object of class "prcomp" with the PCA. In the biplot, "a" denotes the intercept, "b" denotes the parameter that give information about the importance of the bacteria in defining herself in the next time point and "c" denotes denotes the parameter that give information about the importance of the rest of the community in defining the bacteria in the next time point.

Examples

set.seed(123)
especie=t(gtools::rdirichlet(10,c(1,3,1,2,4)))
names=c("Bact1","Bact2","Bact3","Bact4","Bact5")
tau1=0.4
parms1= cbind(c(0.1,0.2,0.4,0.6),c(-0.2,0.1,0.1,0.3),c(0.3,0.2,0.3,0.5))
paramEstimadosFinal=c(as.vector( t(parms1)),tau1)

PCAbiplot(paramEstimadosFinal,names,5)

CoDaLoMic documentation built on April 12, 2025, 2:18 a.m.