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-rw-r--r--R/create_deg_func.R2
-rw-r--r--R/nlme.mmkin.R7
-rw-r--r--R/summary.nlme.mmkin.R2
3 files changed, 6 insertions, 5 deletions
diff --git a/R/create_deg_func.R b/R/create_deg_func.R
index 4b4284db..5794c65c 100644
--- a/R/create_deg_func.R
+++ b/R/create_deg_func.R
@@ -10,8 +10,8 @@
#' m1 = mkinsub("SFO"))
#' FOCUS_D <- subset(FOCUS_2006_D, value != 0) # to avoid warnings
#' fit_1 <- mkinfit(SFO_SFO, FOCUS_D, solution_type = "analytical", quiet = TRUE)
-#' fit_2 <- mkinfit(SFO_SFO, FOCUS_D, solution_type = "deSolve", quiet = TRUE)
#' \dontrun{
+#' fit_2 <- mkinfit(SFO_SFO, FOCUS_D, solution_type = "deSolve", quiet = TRUE)
#' if (require(rbenchmark))
#' benchmark(
#' analytical = mkinfit(SFO_SFO, FOCUS_D, solution_type = "analytical", quiet = TRUE),
diff --git a/R/nlme.mmkin.R b/R/nlme.mmkin.R
index b6b6c830..09cb84b8 100644
--- a/R/nlme.mmkin.R
+++ b/R/nlme.mmkin.R
@@ -59,12 +59,11 @@ get_deg_func <- function() {
#' @examples
#' ds <- lapply(experimental_data_for_UBA_2019[6:10],
#' function(x) subset(x$data[c("name", "time", "value")], name == "parent"))
-#' f <- mmkin(c("SFO", "DFOP"), ds, quiet = TRUE, cores = 1)
-#' library(nlme)
-#' f_nlme_sfo <- nlme(f["SFO", ])
#'
#' \dontrun{
-#'
+#' f <- mmkin(c("SFO", "DFOP"), ds, quiet = TRUE, cores = 1)
+#' library(nlme)
+#' f_nlme_sfo <- nlme(f["SFO", ])
#' f_nlme_dfop <- nlme(f["DFOP", ])
#' anova(f_nlme_sfo, f_nlme_dfop)
#' print(f_nlme_dfop)
diff --git a/R/summary.nlme.mmkin.R b/R/summary.nlme.mmkin.R
index be7f0441..1dd73301 100644
--- a/R/summary.nlme.mmkin.R
+++ b/R/summary.nlme.mmkin.R
@@ -62,11 +62,13 @@
#' n = 1)[[1]]
#' })
#'
+#' \dontrun{
#' # Evaluate using mmkin and nlme
#' library(nlme)
#' f_mmkin <- mmkin("SFO", ds_sfo_syn, quiet = TRUE, error_model = "tc", cores = 1)
#' f_nlme <- nlme(f_mmkin)
#' summary(f_nlme, data = TRUE)
+#' }
#'
#' @export
summary.nlme.mmkin <- function(object, data = FALSE, verbose = FALSE, distimes = TRUE, alpha = 0.05, ...) {

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