Description Usage Arguments Value Examples

Scores of all the covariates present in X, given the vector Y of the response.

1 2 |

`X` |
the matrix (or data.frame) of covariates, dimension n*p (n is the sample size, p the number of covariates). X must have rownames, which are the names of the n subjects (i.e. the user ID of the n subjects). X must have colnames, which are the names of the p covariates. |

`Y` |
the vector of the response, length n. |

`nclust` |
the number of clusters in the covariates dataset X. |

`clusterType` |
to precise the type of cluster of the machine. Possible choices: "PSOCK", or "FORK" (for UNIX or MAC systems, but not for WINDOWS). |

`parallel` |
= TRUE if the calculus are made in parallel (default choice is FALSE). |

a 3-list with: "tree" which is the dendrogram of the data X, "nclust" which is a proposition of the number of clusters in the data X, "result" which is a data.frame with p rows and 2 columns, the first column gives the names of the covariates, the second column is the scores of the covariates.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | ```
library(ClustOfVar)
library(impute)
library(FAMT)
library(VSURF)
library(glmnet)
library(anapuce)
library(qvalue)
set.seed(1)
p <- 40
n <- 30
indexRow <- paste0("patient",1:n)
indexCol <- paste0("G",1:p)
X <- matrix(rnorm(p*n),ncol=p)
colnames(X) <- indexCol
rownames(X) <- indexRow
Y <- c(rep(-1,n/2), rep(1,n/2))
X[,1:4] <- X[,1:4] + matrix(rnorm(n*4, mean=2*Y, sd=1), ncol=4)
Y<-as.factor(Y)
resultat <- ARMADA(X,Y, nclust=1)
## Not run:
X<-toys.data$x
Y<-toys.data$Y
result<-ARMADA(X,Y, nclust=2)
## End(Not run)
``` |

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