Description: Mixture of lOgistic Regressions Parameters (H)Estimation with
(U)Spectral methods. The main methods take d-dimensional inputs and a vector
of binary outputs, and return parameters according to the GLMs mixture model
- (please refer to the package vignette).
+ (General Linear Model). For more details see chapter 3 in the PhD thesis of
+ Mor-Absa Loum: http://www.theses.fr/s156435
Version: 0.2-0
Author: Benjamin Auder <Benjamin.Auder@math.u-psud.fr> [aut,cre],
Mor-Absa Loum <Mor-Absa.Loum@math.u-psud.fr> [aut]
#' @return A list of nf aggregates of N results (matrices).
#'
#' @examples
-#' \dontrun{
+#' \donttest{
#' β <- matrix(c(1,-2,3,1),ncol=2)
#'
#' # Bootstrap + computeMu, morpheus VS flexmix ; assumes fargs first 3 elts X,Y,K
#' @param y Column index of the element inside the aggregated parameter
#'
#' @examples
-#' \dontrun{
+#' \donttest{
#' β <- matrix(c(1,-2,3,1),ncol=2)
#' mr <- multiRun(...) #see bootstrap example in ?multiRun : return lists of mu_hat
#' μ <- normalize(β)