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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

-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 8.01e-02 40.03%
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] = 0.1199
f[CL_iov] = 0.0783

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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