-#' Encapsulated optimization for p (proportions), β and b (regression parameters)
-#'
-#' Optimize the parameters of a mixture of logistic regressions model, possibly using
-#' \code{mu <- computeMu(...)} as a partial starting point.
-#'
-#' @field li Link function, 'logit' or 'probit'
-#' @field X Data matrix of covariables
-#' @field Y Output as a binary vector
-#' @field K Number of populations
-#' @field d Number of dimensions
-#' @field W Weights matrix (iteratively refined)
-#'
+# Encapsulated optimization for p (proportions), β and b (regression parameters)
+#
+# Optimize the parameters of a mixture of logistic regressions model, possibly using
+# \code{mu <- computeMu(...)} as a partial starting point.
+#
+# @field li Link function, 'logit' or 'probit'
+# @field X Data matrix of covariables
+# @field Y Output as a binary vector
+# @field Mhat Vector of empirical moments
+# @field K Number of populations
+# @field n Number of sample points
+# @field d Number of dimensions
+# @field nc Number of cores (OpenMP //)
+# @field W Weights matrix (initialized at identity)
+#