From e0bef15657df1d6cade99cc3f6d8b07fa35792fe Mon Sep 17 00:00:00 2001
From: Johannes Ranke <jranke@uni-bremen.de>
Date: Mon, 8 Jul 2019 18:12:21 +0200
Subject: Adaptations for gmkin

Address winbuilder check problems, update check log, update of static docs
---
 man/AIC.mmkin.Rd |  2 ++
 man/mkinfit.Rd   | 11 ++++++++---
 2 files changed, 10 insertions(+), 3 deletions(-)

(limited to 'man')

diff --git a/man/AIC.mmkin.Rd b/man/AIC.mmkin.Rd
index 08e4cc57..ca3fcf20 100644
--- a/man/AIC.mmkin.Rd
+++ b/man/AIC.mmkin.Rd
@@ -26,6 +26,7 @@
   there are several fits in the column).
 }
 \examples{
+  \dontrun{ # skip, as it takes > 10 s on winbuilder
   f <- mmkin(c("SFO", "FOMC", "DFOP"),
     list("FOCUS A" = FOCUS_2006_A,
          "FOCUS C" = FOCUS_2006_C), cores = 1, quiet = TRUE)
@@ -38,6 +39,7 @@
 
   # For FOCUS C, the more complex models fit better
   AIC(f[, "FOCUS C"])
+  }
 }
 \author{
   Johannes Ranke
diff --git a/man/mkinfit.Rd b/man/mkinfit.Rd
index e7d35e4d..f7dd7009 100644
--- a/man/mkinfit.Rd
+++ b/man/mkinfit.Rd
@@ -31,7 +31,8 @@ mkinfit(mkinmod, observed,
   quiet = FALSE,
   atol = 1e-8, rtol = 1e-10, n.outtimes = 100,
   error_model = c("const", "obs", "tc"),
-  error_model_algorithm = c("d_3", "direct", "twostep", "threestep", "fourstep", "IRLS"),
+  error_model_algorithm = c("d_3", "direct", "twostep", "threestep", "fourstep", "IRLS", 
+                            "OLS"),
   reweight.tol = 1e-8, reweight.max.iter = 10,
   trace_parms = FALSE, ...)
 }
@@ -200,10 +201,14 @@ mkinfit(mkinmod, observed,
     with fixed error model parameters, and finally minimizes the negative
     log-likelihood with free degradation and error model parameters.
 
-    The algorithm "IRLS" starts with unweighted least squares,
-    and then iterates optimization of the error model parameters and subsequent
+    The algorithm "IRLS" (Iteratively Reweighted Least Squares) starts with
+    unweighted least squares, and then iterates optimization of the error model
+    parameters and subsequent
     optimization of the degradation model using those error model parameters,
     until the error model parameters converge.
+
+    The algorithm "OLS" (Ordinary Least Squares) is automatically selected when
+    the error model is "const" and results in an unweighted least squares fit.
   }
   \item{reweight.tol}{
     Tolerance for the convergence criterion calculated from the error model
-- 
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