• Language: en
  • Documentation version: 1.3.1

One Compartment Model with Absorption and Inter-occasion Variance f[CL_isv]=0.5

[Generated automatically as a Tutorial summary]

Model Description

Name:

d1cmp_cl_iov_05

Title:

One Compartment Model with Absorption and Inter-occasion Variance f[CL_isv]=0.5

Author:

PoPy for PK/PD

Abstract:

Population one Compartment Model with Absorption and Inter-occasion Variance
Here f[CL_isv] true value is 0.5
Keywords:

one compartment model; dep_one_cmp_cl; iov

Input Script:

d1cmp_cl_iov_05.pyml

Diagram:

Comparison

True objective value

-375.4831

Final fitted objective value

-384.2726

Compare Main f[X]

Name

Initial

Fitted

True

Abs. Error

Prop. Error

f[KA]

0.5

0.316

0.3

1.56e-02

5.19%

f[CL]

1

2.36

3

6.35e-01

21.17%

f[V]

15

19.7

20

2.77e-01

1.38%

Compare Noise f[X]

Name

Initial

Fitted

True

Abs. Error

Prop. Error

f[PNOISE_STD]

0.2

0.0984

0.1

1.63e-03

1.63%

f[ANOISE_STD]

0.2

0.0486

0.05

1.38e-03

2.75%

Compare Variance f[X]

Name

Initial

Fitted

True

Abs. Error

Prop. Error

f[CL_isv]

0.01

0.303

0.5

1.97e-01

39.43%

f[CL_iov]

0.01

0.00291

0.01

7.09e-03

70.93%

Outputs

Fitted f[X] values (after fitting)

f[KA] = 0.3156
f[CL] = 2.3650
f[V] = 19.7234
f[PNOISE_STD] = 0.0984
f[ANOISE_STD] = 0.0486
f[CL_isv] = 0.3028
f[CL_iov] = 0.0029

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] = 0.5000
f[CL_iov] = 0.0100

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
Back to Top