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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

-352.8548

Final fitted objective value

-365.3290

Compare Main f[X]

Name

Initial

Fitted

True

Abs. Error

Prop. Error

f[KA]

0.5

0.269

0.3

3.14e-02

10.46%

f[CL]

1

2.09

3

9.06e-01

30.19%

f[V]

15

18.2

20

1.83e+00

9.17%

Compare Noise f[X]

Name

Initial

Fitted

True

Abs. Error

Prop. Error

f[PNOISE_STD]

0.2

0.0889

0.1

1.11e-02

11.06%

f[ANOISE_STD]

0.2

0.0486

0.05

1.40e-03

2.79%

Compare Variance f[X]

Name

Initial

Fitted

True

Abs. Error

Prop. Error

f[CL_isv]

0.01

0.283

0.5

2.17e-01

43.31%

f[CL_iov]

0.01

0.0105

0.01

5.18e-04

5.18%

Outputs

Fitted f[X] values (after fitting)

f[KA] = 0.2686
f[CL] = 2.0943
f[V] = 18.1651
f[PNOISE_STD] = 0.0889
f[ANOISE_STD] = 0.0486
f[CL_isv] = 0.2835
f[CL_iov] = 0.0105

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
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