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: | d1cmp_cl_isv_naive.pyml |
| Diagram: |
Comparison¶
True objective value¶
1096.4897
Final fitted objective value¶
-208.2420
Compare Main f[X]¶
| Name | Initial | Fitted | True | Abs. Error | Prop. Error |
|---|---|---|---|---|---|
| f[KA] | 0.5 | 0.334 | 0.3 | 3.41e-02 | 11.36% |
| f[CL] | 1 | 3.24 | 3 | 2.37e-01 | 7.91% |
| f[V] | 15 | 33.3 | 20 | 1.33e+01 | 66.66% |
Compare Noise f[X]¶
| Name | Initial | Fitted | True | Abs. Error | Prop. Error |
|---|---|---|---|---|---|
| f[PNOISE_STD] | 0.2 | 0.596 | 0.1 | 4.96e-01 | 495.79% |
| f[ANOISE_STD] | 0.2 | 0.0886 | 0.05 | 3.86e-02 | 77.17% |
Compare Variance f[X]¶
No Variance f[X] values to compare.
Outputs¶
Fitted f[X] values (after fitting)¶
f[KA] = 0.3341
f[CL] = 3.2372
f[V] = 33.3329
f[PNOISE_STD] = 0.5958
f[ANOISE_STD] = 0.0886
f[CL_isv] = 0.0000
Generated data .csv file¶
| Synthetic Data: | synthetic_data.csv |
|---|
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