aboutsummaryrefslogtreecommitdiff
path: root/docs/reference/synthetic_data_for_UBA.html
diff options
context:
space:
mode:
authorJohannes Ranke <jranke@uni-bremen.de>2018-07-18 15:18:30 +0200
committerJohannes Ranke <jranke@uni-bremen.de>2018-07-18 15:58:46 +0200
commit0b98c459c30a0629a728acf6b311de035c55fb64 (patch)
treef146faf4802da38862aa14b0268265f3fad9ba34 /docs/reference/synthetic_data_for_UBA.html
parentd3ed95f2a0a43ed74b02ea90e35d043ed4e1e72f (diff)
Correct references to the Rocke and Lorenzato model
Rename 'sigma_rl' to 'sigma_twocomp' as the Rocke and Lorenzato model assumes lognormal distribution for large y. Rebuild static documentation.
Diffstat (limited to 'docs/reference/synthetic_data_for_UBA.html')
-rw-r--r--docs/reference/synthetic_data_for_UBA.html12
1 files changed, 9 insertions, 3 deletions
diff --git a/docs/reference/synthetic_data_for_UBA.html b/docs/reference/synthetic_data_for_UBA.html
index 6e0ac227..9d9404e5 100644
--- a/docs/reference/synthetic_data_for_UBA.html
+++ b/docs/reference/synthetic_data_for_UBA.html
@@ -39,7 +39,10 @@ Variance component 'a' is based on a normal distribution with standard deviation
Variance component 'b' is also based on a normal distribution, but with a standard deviation of 7.
Variance component 'c' is based on the error model from Rocke and Lorenzato (1995), with the
minimum standard deviation (for small y values) of 0.5, and a proportionality constant of 0.07
- for the increase of the standard deviation with y.
+ for the increase of the standard deviation with y. Note that this is a simplified version
+ of the error model proposed by Rocke and Lorenzato (1995), as in their model the error of the
+ measured values approximates lognormal distribution for high values, whereas we are using
+ normally distributed error components all along.
Initial concentrations for metabolites and all values where adding the variance component resulted
in a value below the assumed limit of detection of 0.1 were set to NA.
As an example, the first dataset has the title SFO_lin_a and is based on the SFO model
@@ -73,7 +76,7 @@ Compare also the code in the example section to see the degradation models." />
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">mkin</a>
- <span class="label label-default" data-toggle="tooltip" data-placement="bottom" title="Released package">0.9.47.1</span>
+ <span class="label label-default" data-toggle="tooltip" data-placement="bottom" title="Released package">0.9.47.2</span>
</span>
</div>
@@ -142,7 +145,10 @@ Compare also the code in the example section to see the degradation models." />
Variance component 'b' is also based on a normal distribution, but with a standard deviation of 7.
Variance component 'c' is based on the error model from Rocke and Lorenzato (1995), with the
minimum standard deviation (for small y values) of 0.5, and a proportionality constant of 0.07
- for the increase of the standard deviation with y.</p>
+ for the increase of the standard deviation with y. Note that this is a simplified version
+ of the error model proposed by Rocke and Lorenzato (1995), as in their model the error of the
+ measured values approximates lognormal distribution for high values, whereas we are using
+ normally distributed error components all along.</p>
<p>Initial concentrations for metabolites and all values where adding the variance component resulted
in a value below the assumed limit of detection of 0.1 were set to <code>NA</code>.</p>
<p>As an example, the first dataset has the title <code>SFO_lin_a</code> and is based on the SFO model

Contact - Imprint