Basic multistart method for saem.mmkin objects

2 files changed, 42 insertions, 14 deletions

diff --git a/R/multistart.R b/R/multistart.R
index db482cc4..819fcc1b 100644
--- a/R/multistart.R
+++ b/R/multistart.R
@@ -7,18 +7,38 @@
 #' inspired by the article on practical identifiabiliy in the frame of nonlinear
 #' mixed-effects models by Duchesne et al (2021).
 #'
+#' Currently, parallel execution of the fits is only supported using
+#' [parallel::mclapply], i.e. not available on Windows.
+#'
+#' @param object The fit object to work with
+#' @param n How many different combinations of starting parameters should be
+#' used?
+#' @param cores How many fits should be run in parallel?
+#' @param \dots Passed to the update function.
+#' @return A list of [saem.mmkin] objects, with class attributes
+#' 'multistart.saem.mmkin' and 'multistart'.
+#'
 #' @references Duchesne R, Guillemin A, Gandrillon O, Crauste F. Practical
 #' identifiability in the frame of nonlinear mixed effects models: the example
 #' of the in vitro erythropoiesis. BMC Bioinformatics. 2021 Oct 4;22(1):478.
 #' doi: 10.1186/s12859-021-04373-4.
 #' @export
-multistart <- function(object, n = 50, ...)
+multistart <- function(object, n = 50, cores = 1, ...)
 {
   UseMethod("multistart", object)
 }
 
 #' @rdname multistart
 #' @export
-multistart.saem.mmkin <- function(object, n = 50, ...) {
-  
+multistart.saem.mmkin <- function(object, n = 50, cores = 1, ...) {
+  start_parms <- apply(
+    parms(object$mmkin, errparms = FALSE), 1,
+      function(x) stats::runif(n, min(x), max(x))
+  )
+
+  res <- parallel::mclapply(1:n, function(x) {
+    update(object, degparms_start = start_parms[x], ...)
+  }, mc.cores = cores)
+  class(res) <- c("multistart.saem.mmkin", "multistart")
+  return(res)
 }
diff --git a/R/parms.mkinfit.R b/R/parms.mkinfit.R
index a1f2d209..31ca05bc 100644
--- a/R/parms.mkinfit.R
+++ b/R/parms.mkinfit.R
@@ -8,9 +8,9 @@
 #'  [mkinfit()] objects and for [mmkin()] objects.
 #' @param \dots Not used
 #' @return For mkinfit objects, a numeric vector of fitted model parameters.
-#'  For mmkin row objects, a matrix with the parameters with a
-#'  row for each dataset. If the mmkin object has more than one row, a list of
-#'  such matrices is returned.
+#' For mmkin row objects, a matrix with the parameters with a row for each
+#' dataset. If the mmkin object has more than one row, a list of such matrices
+#' is returned.
 #' @examples
 #' # mkinfit objects
 #' fit <- mkinfit("SFO", FOCUS_2006_C, quiet = TRUE)
@@ -34,27 +34,35 @@ parms <- function(object, ...)
   UseMethod("parms", object)
 }
 
-#' @param transformed Should the parameters be returned
-#'   as used internally during the optimisation?
+#' @param transformed Should the parameters be returned as used internally
+#' during the optimisation?
+#' @param errparms Should the error model parameters be returned
+#' in addition to the degradation parameters?
 #' @rdname parms
 #' @export
-parms.mkinfit <- function(object, transformed = FALSE, ...)
+parms.mkinfit <- function(object, transformed = FALSE, errparms = TRUE, ...)
 {
-  if (transformed) object$par
-  else c(object$bparms.optim, object$errparms)
+  res <- if (transformed) object$par
+    else c(object$bparms.optim, object$errparms)
+  if (!errparms) {
+    res[setdiff(names(res), names(object$errparms))]
+  }
+  else return(res)
 }
 
 #' @rdname parms
 #' @export
-parms.mmkin <- function(object, transformed = FALSE, ...)
+parms.mmkin <- function(object, transformed = FALSE, errparms = TRUE, ...)
 {
   if (nrow(object) == 1) {
-    res <- sapply(object, parms, transformed = transformed, ...)
+    res <- sapply(object, parms, transformed = transformed,
+      errparms = errparms, ...)
     colnames(res) <- colnames(object)
   } else {
     res <- list()
     for (i in 1:nrow(object)) {
-      res[[i]] <- parms(object[i, ], transformed = transformed, ...)
+      res[[i]] <- parms(object[i, ], transformed = transformed,
+        errparms = errparms, ...)
     }
     names(res) <- rownames(object)
   }