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/synthetic_data_for_UBA.html | 124 ++++------------------------- 1 file changed, 16 insertions(+), 108 deletions(-) (limited to 'docs/reference/synthetic_data_for_UBA.html') diff --git a/docs/reference/synthetic_data_for_UBA.html b/docs/reference/synthetic_data_for_UBA.html index 1f8bc914..b3da0016 100644 --- a/docs/reference/synthetic_data_for_UBA.html +++ b/docs/reference/synthetic_data_for_UBA.html @@ -16,13 +16,15 @@ - + + - - + + + @@ -62,6 +64,7 @@ Compare also the code in the example section to see the degradation models." /> + @@ -131,6 +134,7 @@ Compare also the code in the example section to see the degradation models." /> +
@@ -170,7 +174,9 @@ Compare also the code in the example section to see the degradation models." /> each containing, among others, the following components

title

The name of the dataset, e.g. SFO_lin_a

data

A data frame with the data in the form expected by mkinfit

-
+ + +

Source

@@ -181,109 +187,7 @@ Compare also the code in the example section to see the degradation models." />

Examples

- 
# The data have been generated using the following kinetic models
-m_synth_SFO_lin <- mkinmod(parent = list(type = "SFO", to = "M1"),
-                           M1 = list(type = "SFO", to = "M2"),
-                           M2 = list(type = "SFO"), use_of_ff = "max")
-
-
-m_synth_SFO_par <- mkinmod(parent = list(type = "SFO", to = c("M1", "M2"),
-                                         sink = FALSE),
-                           M1 = list(type = "SFO"),
-                           M2 = list(type = "SFO"), use_of_ff = "max")
-
-m_synth_DFOP_lin <- mkinmod(parent = list(type = "DFOP", to = "M1"),
-                            M1 = list(type = "SFO", to = "M2"),
-                            M2 = list(type = "SFO"), use_of_ff = "max")
-
-m_synth_DFOP_par <- mkinmod(parent = list(type = "DFOP", to = c("M1", "M2"),
-                                          sink = FALSE),
-                            M1 = list(type = "SFO"),
-                            M2 = list(type = "SFO"), use_of_ff = "max")
-
-# The model predictions without intentional error were generated as follows
-sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
-
-d_synth_SFO_lin <- mkinpredict(m_synth_SFO_lin,
-                               c(k_parent = 0.7, f_parent_to_M1 = 0.8,
-                                 k_M1 = 0.3, f_M1_to_M2 = 0.7,
-                                 k_M2 = 0.02),
-                               c(parent = 100, M1 = 0, M2 = 0),
-                               sampling_times)
-
-d_synth_DFOP_lin <- mkinpredict(m_synth_DFOP_lin,
-                                c(k1 = 0.2, k2 = 0.02, g = 0.5,
-                                  f_parent_to_M1 = 0.5, k_M1 = 0.3,
-                                  f_M1_to_M2 = 0.7, k_M2 = 0.02),
-                                 c(parent = 100, M1 = 0, M2 = 0),
-                                 sampling_times)
-
-d_synth_SFO_par <- mkinpredict(m_synth_SFO_par,
-                               c(k_parent = 0.2,
-                                 f_parent_to_M1 = 0.8, k_M1 = 0.01,
-                                 f_parent_to_M2 = 0.2, k_M2 = 0.02),
-                                 c(parent = 100, M1 = 0, M2 = 0),
-                                 sampling_times)
-
-d_synth_DFOP_par <- mkinpredict(m_synth_DFOP_par,
-                               c(k1 = 0.3, k2 = 0.02, g = 0.7,
-                                 f_parent_to_M1 = 0.6, k_M1 = 0.04,
-                                 f_parent_to_M2 = 0.4, k_M2 = 0.01),
-                                 c(parent = 100, M1 = 0, M2 = 0),
-                                 sampling_times)
-
-# Construct names for datasets with errors
-d_synth_names = paste0("d_synth_", c("SFO_lin", "SFO_par",
-                                     "DFOP_lin", "DFOP_par"))
-
-# Function for adding errors. The add_err function now published with this
-# package is a slightly generalised version where the names of secondary
-# compartments that should have an initial value of zero (M1 and M2 in this
-# case) are not hardcoded any more.
-add_err = function(d, sdfunc, LOD = 0.1, reps = 2, seed = 123456789)
-{
-  set.seed(seed)
-  d_long = mkin_wide_to_long(d, time = "time")
-  d_rep = data.frame(lapply(d_long, rep, each = 2))
-  d_rep$value = rnorm(length(d_rep$value), d_rep$value, sdfunc(d_rep$value))
-
-  d_rep[d_rep$time == 0 & d_rep$name 
-  d_NA <- transform(d_rep, value = ifelse(value < LOD, NA, value))
-  d_NA$value <- round(d_NA$value, 1)
-  return(d_NA)
-}
-
-# The following is the simplified version of the two-component model of Rocke
-# and Lorenzato (1995)
-sdfunc_twocomp = function(value, sd_low, rsd_high) {
-  sqrt(sd_low^2 + value^2 * rsd_high^2)
-}
-
-# Add the errors.
-for (d_synth_name in d_synth_names)
-{
-  d_synth = get(d_synth_name)
-  assign(paste0(d_synth_name, "_a"), add_err(d_synth, function(value) 3))
-  assign(paste0(d_synth_name, "_b"), add_err(d_synth, function(value) 7))
-  assign(paste0(d_synth_name, "_c"), add_err(d_synth,
-                           function(value) sdfunc_twocomp(value, 0.5, 0.07)))
-
-}
-
-d_synth_err_names = c(
-  paste(rep(d_synth_names, each = 3), letters[1:3], sep = "_")
-)
-
-# This is just one example of an evaluation using the kinetic model used for
-# the generation of the data
-fit <- mkinfit(m_synth_SFO_lin, synthetic_data_for_UBA_2014[[1]]$data,
-               quiet = TRUE)
-plot_sep(fit)
-summary(fit)
-
#> Error: <text>:67:43: Unerwartete(s) SPECIAL
-#> 66: 
-#> 67:   d_rep[d_rep$time == 0 & d_rep$name <!-- %in%
-#>                                               ^
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