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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

-392.2101

Final fitted objective value

-398.8099

Compare Main f[X]

Name Initial Fitted True Abs. Error Prop. Error
f[KA] 0.5 0.318 0.3 1.79e-02 5.98%
f[CL] 1 3.33 3 3.33e-01 11.10%
f[V] 15 19.3 20 6.53e-01 3.27%

Compare Noise f[X]

Name Initial Fitted True Abs. Error Prop. Error
f[PNOISE_STD] 0.2 0.0946 0.1 5.42e-03 5.42%
f[ANOISE_STD] 0.2 0.0495 0.05 4.71e-04 0.94%

Compare Variance f[X]

Name Initial Fitted True Abs. Error Prop. Error
f[CL_isv] 0.01 0.146 0.2 5.36e-02 26.82%
f[CL_iov] 0.01 0.0608 0.1 3.92e-02 39.20%

Outputs

Fitted f[X] values (after fitting)

f[KA] = 0.3179
f[CL] = 3.3331
f[V] = 19.3470
f[PNOISE_STD] = 0.0946
f[ANOISE_STD] = 0.0495
f[CL_isv] = 0.1464
f[CL_iov] = 0.0608

Generated data .csv file

Synthetic Data:synthetic_data.csv

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
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