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+## ---- include = FALSE----------------------------------------------------
+require(knitr)
+opts_chunk$set(engine='R', tidy=FALSE)
+
+## ---- echo = TRUE, cache = TRUE, fig = TRUE, fig.width = 8, fig.height = 7----
+library(mkin)
+# Define the kinetic model
+m_SFO_SFO_SFO <- mkinmod(parent = mkinsub("SFO", "M1"),
+ M1 = mkinsub("SFO", "M2"),
+ M2 = mkinsub("SFO"),
+ use_of_ff = "max", quiet = TRUE)
+
+
+# Produce model predictions using some arbitrary parameters
+sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
+d_SFO_SFO_SFO <- mkinpredict(m_SFO_SFO_SFO,
+ c(k_parent = 0.03,
+ f_parent_to_M1 = 0.5, k_M1 = log(2)/100,
+ f_M1_to_M2 = 0.9, k_M2 = log(2)/50),
+ c(parent = 100, M1 = 0, M2 = 0),
+ sampling_times)
+
+# Generate a dataset by adding normally distributed errors with
+# standard deviation 3, for two replicates at each sampling time
+d_SFO_SFO_SFO_err <- add_err(d_SFO_SFO_SFO, reps = 2,
+ sdfunc = function(x) 3,
+ n = 1, seed = 123456789 )
+
+# Fit the model to the dataset
+f_SFO_SFO_SFO <- mkinfit(m_SFO_SFO_SFO, d_SFO_SFO_SFO_err[[1]], quiet = TRUE)
+
+# Plot the results separately for parent and metabolites
+plot_sep(f_SFO_SFO_SFO, lpos = c("topright", "bottomright", "bottomright"))
+

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