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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:

Failed to create compartment diagram

True f[X] values

f[KA] = 0.3
f[CL] = 3
f[V] = 20
f[PNOISE_STD] = 0.1
f[ANOISE_STD] = 0.05
f[CL_isv] = 0.2

Starting f[X] values

f[KA] = 0.5
f[CL] = 1
f[V] = 15
f[PNOISE_STD] = 0.2
f[ANOISE_STD] = 0.2
f[CL_isv] = 0.01

Outputs

Fitted f[X] values

f[KA] = 1
f[CL] = 2.4567
f[V] = 22.048
f[PNOISE_STD] = 0.23467
f[ANOISE_STD] = 0.03752
f[CL_isv] = 0.1284

Plots

Dense comp plots

Alternatively see All dense_comp graph plots

Comparison

True objective value

-362.688042983

Final fitted objective value

-311.99664349

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 2.46 3 18.11% 5.43e-01
f[V] 15 22 20 10.24% 2.05e+00

Compare Noise f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[PNOISE_STD] 0.2 0.235 0.1 134.67% 1.35e-01
f[ANOISE_STD] 0.2 0.0375 0.05 24.96% 1.25e-02

Compare Variance f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[CL_isv] 0.01 0.128 0.2 35.80% 7.16e-02
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