Add of the mcor.partial function estimating the partial correlation coeficients matrix

R/mcov.R

+#' @include procmod.frame.R
+#'
+NULL
+
+#' Compute the variance, covariance matrix of K coordinate matrices.
+#'
+#' Covariance between two matrices is defined as the sum of the
+#' sigular values of the X'Y matrix. All the matrices must have
+#' the same number of rows.
+#'
+#' @param ... the set of matrices
+#'
+#' @examples
+#'    # Build Three matrices of 3 rows.
+#'    A <- matrix(1:9,nrow=3)
+#'    B <- matrix(10:15,nrow=3)
+#'    C <- matrix(20:31,nrow=3)
+#'    # compute the variance covariance matrix
+#'    mvar(A,B,C)
+#'    mvar(A=A,B=B,C=C)
+#'
+#' @author Eric Coissac & Christelle Gonindard-Melodelima
+#' @export
+mvar = function(...) {
+
+  Xs <- list(...)
+  if (length(Xs)==1)
+    if (is.list(Xs[[1]]))
+      Xs=as.procmod.frame(Xs[[1]])
+    else if (is.procmod.frame(Xs[[1]]))
+      Xs=Xs[[1]]
+    else
+      Xs=procmod.frame(Xs[[1]])
+    else
+      Xs=as.procmod.frame(Xs)
+
+    Xnames=names(Xs)
+
+    Xs <- lapply(Xs,scale,scale = FALSE)
+
+    nX = length(Xs)
+
+    Xx <- rep(1:nX,nX)
+    Xy <- rep(1:nX,rep(nX,nX))
+
+    XXs <- mapply(function(x,y) crossprod(Xs[[x]], Xs[[y]]),
+                  Xx,Xy,
+                  SIMPLIFY = FALSE)
+
+    sol_xxs <- lapply(XXs,svd)
+
+    CovXXs  = sapply(sol_xxs, function(sol) sum(sol$d))
+
+
+    dim(CovXXs)=c(nX,nX)
+    colnames(CovXXs)=Xnames
+    rownames(CovXXs)=Xnames
+
+    return(CovXXs)
+}
+
+#' Compute the person correlation matrix of K coordinate matrices
+#'
+#' @author Eric Coissac
+#' @author Christelle Gonindard-Melodelima
+#' @export
+mcor = function(...) {
+  cov = mvar(...)
+  s = sqrt(diag(cov))
+  vv= outer(s,s)
+  return(cov/vv)
+}
+
+#' Compute the person partial correlation matrix of K coordinate matrices
+#'
+#' @author Eric Coissac
+#' @author Christelle Gonindard-Melodelima
+#' @export
+mcor.partial = function(...) {
+  C = solve(mcor(...))
+  D = sqrt(diag(C) %o% diag(C))
+  return(C/D)
+}
+
+