Further adaptations for the logistic model

- Make mmkin compatible
- Return DT50 values corresponding to k0 and kmax
- Turn incompatible parameter names in parms.ini from an error to a
warning, in order to make it possible to use this argument in calls to
mmkin

3 files changed, 9 insertions, 4 deletions

diff --git a/R/endpoints.R b/R/endpoints.R
index 80450185..f8a44c4d 100644
--- a/R/endpoints.R
+++ b/R/endpoints.R
@@ -166,6 +166,11 @@ endpoints <- function(fit) {
       r = parms.all["r"]

       DT50 = (1/r) * log(1 - ((kmax/k0) * (1 - 2^(r/kmax))))

       DT90 = (1/r) * log(1 - ((kmax/k0) * (1 - 10^(r/kmax))))

+

+      DT50_k0 = log(2)/k0

+      DT50_kmax = log(2)/kmax

+      ep$distimes[obs_var, c("DT50_k0")] = DT50_k0

+      ep$distimes[obs_var, c("DT50_kmax")] = DT50_kmax

     }

     ep$distimes[obs_var, c("DT50", "DT90")] = c(DT50, DT90)

   }

diff --git a/R/mkinfit.R b/R/mkinfit.R
index 40413125..2dec3a72 100644
--- a/R/mkinfit.R
+++ b/R/mkinfit.R
@@ -99,10 +99,10 @@ mkinfit <- function(mkinmod, observed,
   # Define starting values for parameters where not specified by the user

   if (parms.ini[[1]] == "auto") parms.ini = vector()

 

-  # Prevent inital parameter specifications that are not in the model

+  # Warn for inital parameter specifications that are not in the model

   wrongpar.names <- setdiff(names(parms.ini), mkinmod$parms)

   if (length(wrongpar.names) > 0) {

-    stop("Initial parameter(s) ", paste(wrongpar.names, collapse = ", "),

+    warning("Initial parameter(s) ", paste(wrongpar.names, collapse = ", "),

          " not used in the model")

   }

 

diff --git a/R/mmkin.R b/R/mmkin.R
index 63542f4f..b713ae74 100644
--- a/R/mmkin.R
+++ b/R/mmkin.R
@@ -1,4 +1,4 @@
-# Copyright (C) 2015 Johannes Ranke
+# Copyright (C) 2015,2019 Johannes Ranke
 # Contact: jranke@uni-bremen.de
 # The summary function is an adapted and extended version of summary.modFit
 # from the FME package, v 1.1 by Soetart and Petzoldt, which was in turn
@@ -22,7 +22,7 @@
 mmkin <- function(models = c("SFO", "FOMC", "DFOP"), datasets,
                   cores = round(detectCores()/2), cluster = NULL, ...)
 {
-  parent_models_available = c("SFO", "FOMC", "DFOP", "HS", "SFORB", "IORE")
+  parent_models_available = c("SFO", "FOMC", "DFOP", "HS", "SFORB", "IORE", "logistic")
   n.m <- length(models)
   n.d <- length(datasets)
   n.fits <- n.m * n.d