MultiGroupO vignette"
In MultiGroupO: MultiGroup Method and Simulation Data Analysis

knitr::opts_chunk$set(
  fig.width=6,
  fig.height=5,
  collapse = TRUE,
  comment = "#"
)

[vignetteMult](vignetteMult.html)
[datR](datR.html "Real Datasets Application")

Introduction

The package contains functions to simulate multigroup data from a multivariate normal with different mean, matrix structures of variances and covariances, it will also consider not only biological signal but also considers noise variables for the different sizes of groups that can be balanced or unbalanced. It also contains functions with the new proposed multigroup methods.

For an overview of supported, methods, and defaults together with some basic examples see

README of the released version on CRAN;
README of the development version on GitHub.

Installation

You can install the development version from GitHub with

# install.packages("remotes")
remotes::install_github("carolina/MultiGroupO")

Contributors

Carolina Millapan (author, maintainer)
Ferran Reverter (author)
Esteban Vegas (author)

Session Information

library(MultiGroupO)
sim.list<-fun.sim(g=c(30,30,30),mean1=2,d=0,sds2=c(1,1,1,1),corr=c(0.5,0.5,0.5,0),
                      n.var=c(20,50))
    datos1 <- as.data.frame(sim.list$x)
    datos1<-subset(datos1,select=-grp)
    grupos <- sim.list$grp
     pca(datos1,grupos,Plot=TRUE,center=TRUE,scale=FALSE)
     mat.to.diag1<-new.cov(datos1,cls=grupos,A=diag(ncol(datos1)))
      mgpca(mat.to.diag=mat.to.diag1,mat.x=as.matrix(datos1),cls=grupos,Plot=T,ncomp=2,center = TRUE,scale = TRUE)

library(MultiGroupO)
sim.list<-fun.sim(g=c(30,30,30),mean1=2,d=0,sds2=c(1,1,1,1),corr=c(0.5,0.5,0.5,0),
                  n.var=c(20,50))
datos1 <- as.data.frame(sim.list$x)
datos1<-subset(datos1,select=-grp)
grupos <- sim.list$grp
mdr(group=grupos,data.x=sim.list$`lisx`,c=2)