- Language: en
Diagonal matrix generation full matrix fit¶
[Generated automatically as a Tutorial summary]
Inputs¶
Description¶
| Name: | gen_diag_fit_full |
|---|---|
| Title: | Diagonal matrix generation full matrix fit |
| Author: | Wright Dose Ltd |
| 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: | gen_diag_fit_full_tut.pyml |
| Diagram: |
True f[X] values¶
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¶
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 ],
]
Outputs¶
Generating and Fitting Summaries¶
- Gen: Diagonal matrix generation full matrix fit (gen)
- Fit: Diagonal matrix generation full matrix fit (fit)
Fitted f[X] values¶
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] = [
[ 0.1767, 0.0096 ],
[ 0.0096, 0.0886 ],
]
Plots¶
Comparison¶
True objective value¶
-2170.8075
Final fitted objective value¶
-2173.3801
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 | Prop. Error | Abs. Error |
|---|---|---|---|---|---|
| f[CL_isv] | 0.01 | 0.177 | 0.2 | 11.63% | 2.33e-02 |
| f[CL_isv;V_isv] | 0.0001 | 0.00963 | 0 | inf | 9.63e-03 |
| f[V_isv;CL_isv] | 0.0001 | 0.00963 | 0 | inf | 9.63e-03 |
| f[V_isv] | 0.01 | 0.0886 | 0.1 | 11.39% | 1.14e-02 |