Population One Compartment Model and Inter-subject Variance

[Generated automatically as a Tutorial summary]

Model Description

Name:: iv_one_cmp_isv
Title:: Population One Compartment Model and Inter-subject Variance
Author:: PoPy for PK/PD
Abstract:

Population One Compartment Model and Inter-subject Variance

Keywords:: one compartment model; iv_one_cmp_k; additive noise
Input Script:: iv_one_cmp_isv.pyml
Diagram:

Comparison

True objective value

1788.9154

Final fitted objective value

1780.5526

Compare Main f[X]

Name	Initial	Fitted	True	Abs. Error	Prop. Error
f[KE]	0.5	0.0753	0.1	2.47e-02	24.73%

Compare Noise f[X]

Name	Initial	Fitted	True	Abs. Error	Prop. Error
f[ANOISE_STD]	100	4.97	5	3.31e-02	0.66%

Compare Variance f[X]

Name	Initial	Fitted	True	Abs. Error	Prop. Error
f[KE_isv]	0.01	0.238	0.2	3.79e-02	18.96%

Outputs

Fitted f[X] values (after fitting)

f[KE] = 0.0753
f[KE_isv] = 0.2379
f[ANOISE_STD] = 4.9669

Generated data .csv file

Synthetic Data:: synthetic_data.csv

Gen and Fit Summaries

Gen: Population One Compartment Model and Inter-subject Variance (gen)
Fit: Population One Compartment Model and Inter-subject Variance (fit)

Inputs

True f[X] values (for simulation)

f[KE] = 0.1000
f[KE_isv] = 0.2000
f[ANOISE_STD] = 5.0000

Starting f[X] values (before fitting)

f[KE] = 0.5000
f[KE_isv] = 0.0100
f[ANOISE_STD] = 100.0000