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One Compartment Model with Absorption and Inter-subject Variance f[CL_isv]=0.2

[Generated automatically as a Tutorial summary]

Inputs

Description

Name:dep_one_cmp_cl_isv
Title:One Compartment Model with Absorption and Inter-subject Variance f[CL_isv]=0.2
Author:Wright Dose Ltd
Abstract:
Population one Compartment Model with Absorption and Inter-subject Variance
Keywords:one compartment model; dep_one_cmp_cl
Input Script:dep_one_cmp_cl_isv.pyml
Diagram:

True f[X] values

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

Starting f[X] values

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

Outputs

Fitted f[X] values

f[KA] = 0.2643
f[CL] = 2.7416
f[V] = 19.1995
f[PNOISE_STD] = 0.1131
f[ANOISE_STD] = 0.0417
f[CL_isv] = 0.1648

Plots

Dense comp plots

Alternatively see All dense_comp graph plots

Comparison

True objective value

-362.6880

Final fitted objective value

-371.3278

Compare Main f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[KA] 0.5 0.264 0.3 11.91% 3.57e-02
f[CL] 1 2.74 3 8.61% 2.58e-01
f[V] 15 19.2 20 4.00% 8.01e-01

Compare Noise f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[PNOISE_STD] 0.2 0.113 0.1 13.11% 1.31e-02
f[ANOISE_STD] 0.2 0.0417 0.05 16.63% 8.32e-03

Compare Variance f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[CL_isv] 0.01 0.165 0.2 17.61% 3.52e-02
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