mixed.mmkin and test coverage

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diff --git a/R/mixed.mmkin.R b/R/mixed.mmkin.R
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+#' Create a mixed effects model from an mmkin row object
+#'
+#' @param object An [mmkin] row object
+#' @param method The method to be used
+#' @param \dots Currently not used
+#' @examples
+#' sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
+#' n_biphasic <- 8
+#' err_1 = list(const = 1, prop = 0.07)
+#'
+#' DFOP_SFO <- mkinmod(
+#'   parent = mkinsub("DFOP", "m1"),
+#'   m1 = mkinsub("SFO"),
+#'   quiet = TRUE)
+#'
+#' set.seed(123456)
+#' log_sd <- 0.3
+#' syn_biphasic_parms <- as.matrix(data.frame(
+#'   k1 = rlnorm(n_biphasic, log(0.05), log_sd),
+#'   k2 = rlnorm(n_biphasic, log(0.01), log_sd),
+#'   g = plogis(rnorm(n_biphasic, 0, log_sd)),
+#'   f_parent_to_m1 = plogis(rnorm(n_biphasic, 0, log_sd)),
+#'   k_m1 = rlnorm(n_biphasic, log(0.002), log_sd)))
+#'
+#' ds_biphasic_mean <- lapply(1:n_biphasic,
+#'   function(i) {
+#'     mkinpredict(DFOP_SFO, syn_biphasic_parms[i, ],
+#'       c(parent = 100, m1 = 0), sampling_times)
+#'   }
+#' )
+#'
+#' set.seed(123456L)
+#' ds_biphasic <- lapply(ds_biphasic_mean, function(ds) {
+#'   add_err(ds,
+#'     sdfunc = function(value) sqrt(err_1$const^2 + value^2 * err_1$prop^2),
+#'     n = 1, secondary = "m1")[[1]]
+#' })
+#'
+#' \dontrun{
+#' f_mmkin <- mmkin(list("DFOP-SFO" = DFOP_SFO), ds_biphasic, error_model = "tc", quiet = TRUE)
+#'
+#' f_mixed <- mixed(f_mmkin)
+#' print(f_mixed)
+#' plot(f_mixed)
+#' }
+#' @export
+mixed <- function(object, ...) {
+  UseMethod("mixed")
+}
+
+#' @export
+#' @rdname mixed
+mixed.mmkin <- function(object, method = c("none"), ...) {
+  if (nrow(object) > 1) stop("Only row objects allowed")
+
+  method <- match.arg(method)
+  if (method == "default") method = c("naive", "nlme")
+
+  ds_names <- colnames(object)
+  res <- list(mmkin = object, mkinmod = object[[1]]$mkinmod)
+
+  if (method[1] == "none") {
+    ds_list <- lapply(object,
+      function(x) x$data[c("variable", "time", "observed", "predicted", "residual")])
+
+    names(ds_list) <- ds_names
+    res$data <- purrr::map_dfr(ds_list, function(x) x, .id = "ds")
+    names(res$data)[1:4] <- c("ds", "name", "time", "value")
+    res$data$name <- as.character(res$data$name)
+    res$data$ds <- ordered(res$data$ds, levels = unique(res$data$ds))
+    standardized <- unlist(lapply(object, residuals, standardized = TRUE))
+    res$data$std <- res$data$residual / standardized
+    res$data$standardized <- standardized
+
+    class(res) <- c("mixed.mmkin")
+    return(res)
+  }
+}
+
+#' @export
+#' @rdname mixed
+#' @param x A mixed.mmkin object to print
+#' @param digits Number of digits to use for printing.
+print.mixed.mmkin <- function(x, digits = max(3, getOption("digits") - 3), ...) {
+  cat("Kinetic model fitted by nonlinear regression to each dataset" )
+  cat("\nStructural model:\n")
+  diffs <- x$mmkin[[1]]$mkinmod$diffs
+  nice_diffs <- gsub("^(d.*) =", "\\1/dt =", diffs)
+  writeLines(strwrap(nice_diffs, exdent = 11))
+  cat("\nData:\n")
+  cat(nrow(x$data), "observations of",
+    length(unique(x$data$name)), "variable(s) grouped in",
+    length(unique(x$data$ds)), "datasets\n\n")
+
+  print(x$mmkin)
+
+  cat("\nMean fitted parameters:\n")
+  print(mean_degparms(x$mmkin))
+
+  invisible(x)
+}