Diagonal matrix generation full matrix fit
[Generated automatically as a Tutorial summary]
Model Description
- Name:
gen_diag_fit_full
- Title:
Diagonal matrix generation full matrix fit
- Author:
PoPy for PK/PD
- Abstract:
One compartment model with absorption compartment and CL/V parametrisation.
This script uses a diagonal covariance matrix to generate the data and a full covariance matrix to fit.
- Keywords:
dep_one_cmp_cl; one compartment model; diagonal matrix; full matrix
- Input Script:
- Diagram:
Comparison
True objective value
-2170.8804
Final fitted objective value
-2173.3583
Compare Main f[X]
No Main f[X] values to compare.
Compare Noise f[X]
No Noise f[X] values to compare.
Compare Variance f[X]
Name |
Initial |
Fitted |
True |
Abs. Error |
Prop. Error |
|---|---|---|---|---|---|
f[CL_isv] |
0.01 |
0.18 |
0.2 |
1.96e-02 |
9.79% |
f[CL_isv;V_isv] |
0.0001 |
0.00867 |
0 |
8.67e-03 |
inf |
f[V_isv;CL_isv] |
0.0001 |
0.00867 |
0 |
8.67e-03 |
inf |
f[V_isv] |
0.01 |
0.0885 |
0.1 |
1.15e-02 |
11.45% |
Outputs
Fitted f[X] values (after fitting)
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,V_isv] = [
[ 0.1804, 0.0087 ],
[ 0.0087, 0.0885 ],
]
Generated data .csv file
- Synthetic Data:
Gen and Fit Summaries
Gen: Diagonal matrix generation full matrix fit (gen)
Fit: Diagonal matrix generation full matrix fit (fit)
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,V_isv] = [
[ 0.2000, 0.0000 ],
[ 0.0000, 0.1000 ],
]
Starting f[X] values (before fitting)
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,V_isv] = [
[ 0.0100, 0.0001 ],
[ 0.0001, 0.0100 ],
]