- Language: en
Full matrix generation diagonal matrix fit¶
[Generated automatically as a Tutorial summary]
Inputs¶
Description¶
Name: | gen_full_fit_diag |
---|---|
Title: | Full matrix generation diagonal matrix fit |
Author: | Wright Dose Ltd |
Abstract: |
One compartment model with absorption compartment and CL/V parametrisation.
This script uses a full covariance matrix to generate the data, but a diagonal matrix to fit.
Keywords: | dep_one_cmp_cl; one compartment model; diagonal matrix; full matrix |
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Input Script: | gen_full_fit_diag_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] = [
[ 0.1500, 0.0500 ],
[ 0.0500, 0.1500 ],
]
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, 0.0000 ],
[ 0.0000, 0.0100 ],
]
Outputs¶
Generating and Fitting Summaries¶
- Gen: Full matrix generation diagonal matrix fit (gen)
- Fit: Full matrix generation diagonal 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] = [
[ 0.1265, 0.0000 ],
[ 0.0000, 0.1185 ],
]
Plots¶
Comparison¶
True objective value¶
-2181.8673
Final fitted objective value¶
-2188.1525
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 | 0.126 | 0.15 | 15.68% | 2.35e-02 |
f[CL_isv;V_isv] | 0 | 0 | 0.05 | 100.00% | 5.00e-02 |
f[V_isv;CL_isv] | 0 | 0 | 0.05 | 100.00% | 5.00e-02 |
f[V_isv] | 0.01 | 0.119 | 0.15 | 20.98% | 3.15e-02 |