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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] = 1.0000
f[CL] = 2.5556
f[V] = 22.1555
f[PNOISE_STD] = 0.2308
f[ANOISE_STD] = 0.0372
f[CL_isv] = 0.1279

Plots

Dense comp plots

Alternatively see All dense_comp graph plots

Comparison

True objective value

-362.6880

Final fitted objective value

-311.6031

Compare Main f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[KA] 0.5 1 0.3 233.33% 7.00e-01
f[CL] 1 2.56 3 14.81% 4.44e-01
f[V] 15 22.2 20 10.78% 2.16e+00

Compare Noise f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[PNOISE_STD] 0.2 0.231 0.1 130.77% 1.31e-01
f[ANOISE_STD] 0.2 0.0372 0.05 25.68% 1.28e-02

Compare Variance f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[CL_isv] 0.01 0.128 0.2 36.05% 7.21e-02
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