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  • Documentation version: 1.3.1

One Compartment Model with Absorption and no inter-occasion Variance f[CL_iov]=0

[Generated automatically as a Tutorial summary]

Model Description

Name:

d1cmp_cl_iov_naive

Title:

One Compartment Model with Absorption and no inter-occasion Variance f[CL_iov]=0

Author:

PoPy for PK/PD

Abstract:

Population one Compartment Model with Absorption and Inter-occasion Variance
Here f[CL_iov] is not estimated it is set to zero.
Keywords:

one compartment model; dep_one_cmp_cl; iov

Input Script:

d1cmp_cl_iov_naive.pyml

Diagram:

Comparison

True objective value

-43.9474

Final fitted objective value

-253.7337

Compare Main f[X]

Name

Initial

Fitted

True

Abs. Error

Prop. Error

f[KA]

0.5

0.32

0.3

2.02e-02

6.74%

f[CL]

1

2.53

3

4.65e-01

15.50%

f[V]

15

21

20

9.76e-01

4.88%

Compare Noise f[X]

Name

Initial

Fitted

True

Abs. Error

Prop. Error

f[PNOISE_STD]

0.2

0.23

0.1

1.30e-01

129.67%

f[ANOISE_STD]

0.2

0.0976

0.05

4.76e-02

95.13%

Compare Variance f[X]

Name

Initial

Fitted

True

Abs. Error

Prop. Error

f[CL_isv]

0.01

0.14

0.2

6.05e-02

30.25%

Outputs

Fitted f[X] values (after fitting)

f[KA] = 0.3202
f[CL] = 2.5349
f[V] = 20.9761
f[PNOISE_STD] = 0.2297
f[ANOISE_STD] = 0.0976
f[CL_isv] = 0.1395
f[CL_iov] = 0.0000

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] = 0.0000
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