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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] = 2.2896
f[V] = 19.5314
f[PNOISE_STD] = 0.2402
f[ANOISE_STD] = 0.0368
f[CL_isv] = 0.1252

Plots

Dense comp plots

Alternatively see All dense_comp graph plots

Comparison

True objective value

-362.6877

Final fitted objective value

-307.5014

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 2.29 3 23.68% 7.10e-01
f[V] 15 19.5 20 2.34% 4.69e-01

Compare Noise f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[PNOISE_STD] 0.2 0.24 0.1 140.20% 1.40e-01
f[ANOISE_STD] 0.2 0.0368 0.05 26.49% 1.32e-02

Compare Variance f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[CL_isv] 0.01 0.125 0.2 37.40% 7.48e-02
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