Additional algorithm "d_c", more tests, docs

The new algorithm tries direct optimization of the likelihood, as well
as a three step procedure. In this way, we consistently get the
model with the highest likelihood for SFO, DFOP and HS for all 12
new test datasets.

1 files changed, 2 insertions, 0 deletions

diff --git a/man/mkinerrplot.Rd b/man/mkinerrplot.Rd
index 4cbb5eb7..3b557b0a 100644
--- a/man/mkinerrplot.Rd
+++ b/man/mkinerrplot.Rd
@@ -68,8 +68,10 @@
  \code{\link{mkinplot}}, for a way to plot the data and the fitted lines of the
  mkinfit object.  }
 \examples{
+\dontrun{
 model <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"))
 fit <- mkinfit(model, FOCUS_2006_D, error_model = "tc", quiet = TRUE)
 mkinerrplot(fit)
 }
+}
 \keyword{ hplot }