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

[Generated automatically as a Tutorial summary]

Model Description

Name:

d1cmp_cl_iov

Title:

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

Author:

PoPy for PK/PD

Abstract:

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

one compartment model; dep_one_cmp_cl; iov

Input Script:

d1cmp_cl_iov.pyml

Diagram:

Comparison

True objective value

-358.2450

Final fitted objective value

-363.8118

Compare Main f[X]

Name

Initial

Fitted

True

Abs. Error

Prop. Error

f[KA]

0.5

0.335

0.3

3.45e-02

11.51%

f[CL]

1

2.59

3

4.15e-01

13.82%

f[V]

15

20.2

20

2.05e-01

1.03%

Compare Noise f[X]

Name

Initial

Fitted

True

Abs. Error

Prop. Error

f[PNOISE_STD]

0.2

0.1…

0.1

3.15e-05

0.03%

f[ANOISE_STD]

0.2

0.0479

0.05

2.10e-03

4.20%

Compare Variance f[X]

Name

Initial

Fitted

True

Abs. Error

Prop. Error

f[CL_isv]

0.01

0.12

0.2

8.00e-02

40.02%

f[CL_iov]

0.01

0.0783

0.1

2.17e-02

21.69%

Outputs

Fitted f[X] values (after fitting)

f[KA] = 0.3345
f[CL] = 2.5855
f[V] = 20.2051
f[PNOISE_STD] = 0.1000
f[ANOISE_STD] = 0.0479
f[CL_isv] = 0.1200
f[CL_iov] = 0.0783

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
f[CL_iov] = 0.1000

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
f[CL_iov] = 0.0100