From e05656d57668688b971c28e32b4cfd4d3eac4662 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Wed, 18 Sep 2019 13:03:50 +0200 Subject: Correct and rebuild docs - Reconcile docs and code for max_twa_parent - Correct links to docs in twa vignette - Static documentation rebuilt by pkgdown --- docs/reference/add_err.html | 39 +++++++++++++++++++++++++-------------- 1 file changed, 25 insertions(+), 14 deletions(-) (limited to 'docs/reference/add_err.html') diff --git a/docs/reference/add_err.html b/docs/reference/add_err.html index cf873540..eeaf9e5b 100644 --- a/docs/reference/add_err.html +++ b/docs/reference/add_err.html @@ -16,13 +16,15 @@ - + + - - + + + @@ -49,6 +51,7 @@ + @@ -118,6 +121,7 @@ +
@@ -136,7 +140,7 @@
- 
add_err(prediction, sdfunc, secondary = c("M1", "M2"),
+    
add_err(prediction, sdfunc, secondary = c("M1", "M2"),
           n = 1000, LOD = 0.1, reps = 2,
           digits = 1, seed = NA)

     
@@ -198,14 +202,14 @@
 m_SFO_SFO <- mkinmod(parent = mkinsub("SFO", "M1"),
                      M1 = mkinsub("SFO"), use_of_ff = "max")
#> Successfully compiled differential equation model from auto-generated C code.

 # Generate a prediction for a specific set of parameters
-sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
+sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
 
 # This is the prediction used for the "Type 2 datasets" on the Piacenza poster
 # from 2015
 d_SFO_SFO <- mkinpredict(m_SFO_SFO,
-                         c(k_parent = 0.1, f_parent_to_M1 = 0.5,
-                           k_M1 = log(2)/1000),
-                         c(parent = 100, M1 = 0),
+                         c(k_parent = 0.1, f_parent_to_M1 = 0.5,
+                           k_M1 = log(2)/1000),
+                         c(parent = 100, M1 = 0),
                          sampling_times)
 
 # Add an error term with a constant (independent of the value) standard deviation
@@ -213,22 +217,25 @@
 d_SFO_SFO_err <- add_err(d_SFO_SFO, function(x) 10, n = 3, seed = 123456789 )
 
 # Name the datasets for nicer plotting
-names(d_SFO_SFO_err) <- paste("Dataset", 1:3)
+names(d_SFO_SFO_err) <- paste("Dataset", 1:3)
 
 # Name the model in the list of models (with only one member in this case) for
 # nicer plotting later on.  Be quiet and use only one core not to offend CRAN
-# checks
f_SFO_SFO <- mmkin(list("SFO-SFO" = m_SFO_SFO),
+# checks
+# \dontrun{
+f_SFO_SFO <- mmkin(list("SFO-SFO" = m_SFO_SFO),
                    d_SFO_SFO_err, cores = 1,
                    quiet = TRUE)
 
-plot(f_SFO_SFO)

+plot(f_SFO_SFO)

 # We would like to inspect the fit for dataset 3 more closely
 # Using double brackets makes the returned object an mkinfit object
 # instead of a list of mkinfit objects, so plot.mkinfit is used
-plot(f_SFO_SFO[[3]], show_residuals = TRUE)

+plot(f_SFO_SFO[[3]], show_residuals = TRUE)

 # If we use single brackets, we should give two indices (model and dataset),
 # and plot.mmkin is used
-plot(f_SFO_SFO[1, 3])
+plot(f_SFO_SFO[1, 3])
# } +
+ + + -- cgit v1.2.1