First order absorption model with peripheral compartment
[Generated automatically as a Tutorial summary]
Model Description
- Name:
builtin_tut_example
- Title:
First order absorption model with peripheral compartment
- Author:
PoPy for PK/PD
- Abstract:
- Keywords:
tutorial; pk; advan4; dep_two_cmp; first order
- Input Script:
- Diagram:
Comparison
True objective value
-873.1410
Final fitted objective value
-893.4004
Compare Main f[X]
Name |
Initial |
Fitted |
True |
Abs. Error |
Prop. Error |
|---|---|---|---|---|---|
f[KA] |
1 |
0.178 |
0.2 |
2.24e-02 |
11.21% |
f[CL] |
1 |
2.05 |
2 |
5.00e-02 |
2.50% |
f[V1] |
20 |
46.6 |
50 |
3.37e+00 |
6.73% |
f[Q] |
0.5 |
1.28 |
1 |
2.84e-01 |
28.39% |
f[V2] |
100 |
58.2 |
80 |
2.18e+01 |
27.19% |
Compare Noise f[X]
Name |
Initial |
Fitted |
True |
Abs. Error |
Prop. Error |
|---|---|---|---|---|---|
f[PNOISE] |
0.1 |
0.144 |
0.15 |
6.42e-03 |
4.28% |
Compare Variance f[X]
Name |
Initial |
Fitted |
True |
Abs. Error |
Prop. Error |
|---|---|---|---|---|---|
f[KA_isv] |
0.05 |
0.0748 |
0.1 |
2.52e-02 |
25.25% |
f[KA_isv;CL_isv] |
0.01 |
0.0819 |
0.01 |
7.19e-02 |
719.18% |
f[KA_isv;V1_isv] |
0.01 |
0.00189 |
0.01 |
8.11e-03 |
81.12% |
f[KA_isv;Q_isv] |
0.01 |
-0.131 |
0.01 |
1.41e-01 |
1408.16% |
f[KA_isv;V2_isv] |
0.01 |
-0.102 |
0.01 |
1.12e-01 |
1122.09% |
f[CL_isv;KA_isv] |
0.01 |
0.0819 |
0.01 |
7.19e-02 |
719.18% |
f[CL_isv] |
0.05 |
0.146 |
0.03 |
1.16e-01 |
385.29% |
f[CL_isv;V1_isv] |
0.01 |
0.0117 |
-0.01 |
2.17e-02 |
216.54% |
f[CL_isv;Q_isv] |
0.01 |
-0.112 |
0.02 |
1.32e-01 |
660.94% |
f[CL_isv;V2_isv] |
0.01 |
-0.279 |
0.02 |
2.99e-01 |
1494.52% |
f[V1_isv;KA_isv] |
0.01 |
0.00189 |
0.01 |
8.11e-03 |
81.12% |
f[V1_isv;CL_isv] |
0.01 |
0.0117 |
-0.01 |
2.17e-02 |
216.54% |
f[V1_isv] |
0.05 |
0.0874 |
0.09 |
2.63e-03 |
2.92% |
f[V1_isv;Q_isv] |
0.01 |
0.0452 |
0.01 |
3.52e-02 |
351.71% |
f[V1_isv;V2_isv] |
0.01 |
0.0315 |
0.01 |
2.15e-02 |
214.62% |
f[Q_isv;KA_isv] |
0.01 |
-0.131 |
0.01 |
1.41e-01 |
1408.16% |
f[Q_isv;CL_isv] |
0.01 |
-0.112 |
0.02 |
1.32e-01 |
660.94% |
f[Q_isv;V1_isv] |
0.01 |
0.0452 |
0.01 |
3.52e-02 |
351.71% |
f[Q_isv] |
0.05 |
0.283 |
0.07 |
2.13e-01 |
304.57% |
f[Q_isv;V2_isv] |
0.01 |
0.0825 |
0.01 |
7.25e-02 |
724.65% |
f[V2_isv;KA_isv] |
0.01 |
-0.102 |
0.01 |
1.12e-01 |
1122.09% |
f[V2_isv;CL_isv] |
0.01 |
-0.279 |
0.02 |
2.99e-01 |
1494.52% |
f[V2_isv;V1_isv] |
0.01 |
0.0315 |
0.01 |
2.15e-02 |
214.62% |
f[V2_isv;Q_isv] |
0.01 |
0.0825 |
0.01 |
7.25e-02 |
724.65% |
f[V2_isv] |
0.05 |
0.772 |
0.05 |
7.22e-01 |
1444.85% |
Outputs
Fitted f[X] values (after fitting)
f[KA] = 0.1776
f[CL] = 2.0500
f[V1] = 46.6326
f[Q] = 1.2839
f[V2] = 58.2479
f[KA_isv,CL_isv,V1_isv,Q_isv,V2_isv] = [
[ 0.0748, 0.0819, 0.0019, -0.1308, -0.1022 ],
[ 0.0819, 0.1456, 0.0117, -0.1122, -0.2789 ],
[ 0.0019, 0.0117, 0.0874, 0.0452, 0.0315 ],
[ -0.1308, -0.1122, 0.0452, 0.2832, 0.0825 ],
[ -0.1022, -0.2789, 0.0315, 0.0825, 0.7724 ],
]
f[PNOISE] = 0.1436
Generated data .csv file
- Synthetic Data:
Gen and Fit Summaries
Inputs
True f[X] values (for simulation)
f[KA] = 0.2000
f[CL] = 2.0000
f[V1] = 50.0000
f[Q] = 1.0000
f[V2] = 80.0000
f[KA_isv,CL_isv,V1_isv,Q_isv,V2_isv] = [
[ 0.1000, 0.0100, 0.0100, 0.0100, 0.0100 ],
[ 0.0100, 0.0300, -0.0100, 0.0200, 0.0200 ],
[ 0.0100, -0.0100, 0.0900, 0.0100, 0.0100 ],
[ 0.0100, 0.0200, 0.0100, 0.0700, 0.0100 ],
[ 0.0100, 0.0200, 0.0100, 0.0100, 0.0500 ],
]
f[PNOISE] = 0.1500
Starting f[X] values (before fitting)
f[KA] = 1.0000
f[CL] = 1.0000
f[V1] = 20.0000
f[Q] = 0.5000
f[V2] = 100.0000
f[KA_isv,CL_isv,V1_isv,Q_isv,V2_isv] = [
[ 0.0500, 0.0100, 0.0100, 0.0100, 0.0100 ],
[ 0.0100, 0.0500, 0.0100, 0.0100, 0.0100 ],
[ 0.0100, 0.0100, 0.0500, 0.0100, 0.0100 ],
[ 0.0100, 0.0100, 0.0100, 0.0500, 0.0100 ],
[ 0.0100, 0.0100, 0.0100, 0.0100, 0.0500 ],
]
f[PNOISE] = 0.1000