• Language: en
  • Documentation version: 1.3.1

One Compartment Model with Absorption and Inter-subject Variance f[CL_isv]=0.2

[Generated automatically as a Tutorial summary]

Model Description

Name:

d1cmp_cl_isv

Title:

One Compartment Model with Absorption and Inter-subject Variance f[CL_isv]=0.2

Author:

PoPy for PK/PD

Abstract:

Population one Compartment Model with Absorption and Inter-subject Variance
Keywords:

one compartment model; dep_one_cmp_cl

Input Script:

d1cmp_cl_isv.pyml

Diagram:

Comparison

True objective value

-389.4976

Final fitted objective value

-394.5900

Compare Main f[X]

Name

Initial

Fitted

True

Abs. Error

Prop. Error

f[KA]

0.5

0.302

0.3

1.93e-03

0.64%

f[CL]

1

3.3

3

2.98e-01

9.94%

f[V]

15

19.7

20

3.50e-01

1.75%

Compare Noise f[X]

Name

Initial

Fitted

True

Abs. Error

Prop. Error

f[PNOISE_STD]

0.2

0.0712

0.1

2.88e-02

28.78%

f[ANOISE_STD]

0.2

0.0545

0.05

4.48e-03

8.97%

Compare Variance f[X]

Name

Initial

Fitted

True

Abs. Error

Prop. Error

f[CL_isv]

0.01

0.184

0.2

1.56e-02

7.80%

Outputs

Fitted f[X] values (after fitting)

f[KA] = 0.3019
f[CL] = 3.2981
f[V] = 19.6503
f[PNOISE_STD] = 0.0712
f[ANOISE_STD] = 0.0545
f[CL_isv] = 0.1844

Generated data .csv file

Synthetic Data:

synthetic_data.csv

Gen and Fit Summaries

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] = 0.2000

Starting f[X] values (before fitting)

f[KA] = 0.5000
f[CL] = 1.0000
f[V] = 15.0000
f[PNOISE_STD] = 0.2000
f[ANOISE_STD] = 0.2000
f[CL_isv] = 0.0100
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