• Language: en

Full matrix generation full matrix fit

[Generated automatically as a Tutorial summary]

Model Description

Name:gen_full_fit_full
Title:Full 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 full covariance matrix to generate the data and a full covariance matrix to fit.
Keywords:dep_one_cmp_cl; one compartment model; full matrix
Input Script:gen_full_fit_full_tut.pyml
Diagram:

Comparison

True objective value

-2106.7004

Final fitted objective value

-2108.2792

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 0.136 0.15 1.39e-02 9.29%
f[CL_isv;V_isv] 0.001 0.05… 0.05 6.60e-06 0.01%
f[V_isv;CL_isv] 0.001 0.05… 0.05 6.60e-06 0.01%
f[V_isv] 0.01 0.166 0.15 1.60e-02 10.66%

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] = [
    [ 0.1361, 0.0500 ],
    [ 0.0500, 0.1660 ],
]

Generated data .csv file

Synthetic Data:synthetic_data.csv

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] = [
    [ 0.1500, 0.0500 ],
    [ 0.0500, 0.1500 ],
]

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, 0.0010 ],
    [ 0.0010, 0.0100 ],
]
Back to Top