One Compartment Model with Absorption and no inter-subject Variance f[CL_isv]=0
[Generated automatically as a Tutorial summary]
Model Description
- Name:
d1cmp_cl_isv_naive
- Title:
One Compartment Model with Absorption and no inter-subject Variance f[CL_isv]=0
- Author:
PoPy for PK/PD
- Abstract:
Population one Compartment Model with Absorption and Inter-subject Variance
Here f[CL_isv] is not estimated it is set to zero.
- Keywords:
one compartment model; dep_one_cmp_cl
- Input Script:
- Diagram:
Comparison
True objective value
787.9714
Final fitted objective value
-200.9398
Compare Main f[X]
Name |
Initial |
Fitted |
True |
Abs. Error |
Prop. Error |
|---|---|---|---|---|---|
f[KA] |
0.5 |
0.209 |
0.3 |
9.13e-02 |
30.45% |
f[CL] |
1 |
3.1 |
3 |
9.63e-02 |
3.21% |
f[V] |
15 |
14.8 |
20 |
5.19e+00 |
25.93% |
Compare Noise f[X]
Name |
Initial |
Fitted |
True |
Abs. Error |
Prop. Error |
|---|---|---|---|---|---|
f[PNOISE_STD] |
0.2 |
0.377 |
0.1 |
2.77e-01 |
276.60% |
f[ANOISE_STD] |
0.2 |
0.162 |
0.05 |
1.12e-01 |
223.72% |
Compare Variance f[X]
No Variance f[X] values to compare.
Outputs
Fitted f[X] values (after fitting)
f[KA] = 0.2087
f[CL] = 3.0963
f[V] = 14.8134
f[PNOISE_STD] = 0.3766
f[ANOISE_STD] = 0.1619
f[CL_isv] = 0.0000
Generated data .csv file
- Synthetic Data:
Gen and Fit Summaries
Inputs
True f[X] values (for simulation)
f[KA] = 0.3000
f[CL] = 3.0000
f[V] = 20.0000
f[PNOISE_STD] = 0.1000
f[ANOISE_STD] = 0.0500
f[CL_isv] = 0.2000
Starting f[X] values (before fitting)
f[KA] = 0.5000
f[CL] = 1.0000
f[V] = 15.0000
f[PNOISE_STD] = 0.2000
f[ANOISE_STD] = 0.2000
f[CL_isv] = 0.0000