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
2777.3504
Final fitted objective value
-163.1359
Compare Main f[X]
Name |
Initial |
Fitted |
True |
Abs. Error |
Prop. Error |
|---|---|---|---|---|---|
f[KA] |
0.5 |
0.182 |
0.3 |
1.18e-01 |
39.38% |
f[CL] |
1 |
2.55 |
3 |
4.48e-01 |
14.94% |
f[V] |
15 |
20.1 |
20 |
1.44e-01 |
0.72% |
Compare Noise f[X]
Name |
Initial |
Fitted |
True |
Abs. Error |
Prop. Error |
|---|---|---|---|---|---|
f[PNOISE_STD] |
0.2 |
0.497 |
0.1 |
3.97e-01 |
396.53% |
f[ANOISE_STD] |
0.2 |
0.128 |
0.05 |
7.79e-02 |
155.81% |
Compare Variance f[X]
No Variance f[X] values to compare.
Outputs
Fitted f[X] values (after fitting)
f[KA] = 0.1818
f[CL] = 2.5519
f[V] = 20.1441
f[PNOISE_STD] = 0.4965
f[ANOISE_STD] = 0.1279
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