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 |
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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 |
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Input Script: | d1cmp_cl_isv_naive.pyml |
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 | 9.14e-02 | 30.45% |
f[CL] | 1 | 3.1 | 3 | 9.63e-02 | 3.21% |
f[V] | 15 | 14.8 | 20 | 5.19e+00 | 25.95% |
Compare Noise f[X]¶
Name | Initial | Fitted | True | Abs. Error | Prop. Error |
---|---|---|---|---|---|
f[PNOISE_STD] | 0.2 | 0.377 | 0.1 | 2.77e-01 | 276.69% |
f[ANOISE_STD] | 0.2 | 0.162 | 0.05 | 1.12e-01 | 223.71% |
Compare Variance f[X]¶
No Variance f[X] values to compare.
Outputs¶
Fitted f[X] values (after fitting)¶
f[KA] = 0.2086
f[CL] = 3.0963
f[V] = 14.8105
f[PNOISE_STD] = 0.3767
f[ANOISE_STD] = 0.1619
f[CL_isv] = 0.0000
Generated data .csv file¶
Synthetic Data: | synthetic_data.csv |
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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