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One Compartment Model with Absorption and no inter-subject Variance f[CL_isv]=0

[Generated automatically as a Tutorial summary]

Inputs

Description

Name:d1cmp_cl_isv_naive
Title:One Compartment Model with Absorption and no inter-subject Variance f[CL_isv]=0
Author:Wright Dose Ltd
Abstract:
Population one Compartment Model with Absorption and Inter-subject Variance
Here f[CL_isv] is not estimated it is set to zero.
Keywords:one compartment model; dep_one_cmp_cl
Input Script:d1cmp_cl_isv_naive.pyml
Diagram:

Failed to create compartment 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] = 0.0000

Outputs

Fitted f[X] values

f[KA] = 0.2087
f[CL] = 3.0963
f[V] = 14.8138
f[PNOISE_STD] = 0.3766
f[ANOISE_STD] = 0.1619
f[CL_isv] = 0.0000

Plots

Dense comp plots

Alternatively see All dense_comp graph plots

Comparison

True objective value

787.9714

Final fitted objective value

-200.9398

Compare Main f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[KA] 0.5 0.209 0.3 30.44% 9.13e-02
f[CL] 1 3.1 3 3.21% 9.63e-02
f[V] 15 14.8 20 25.93% 5.19e+00

Compare Noise f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[PNOISE_STD] 0.2 0.377 0.1 276.65% 2.77e-01
f[ANOISE_STD] 0.2 0.162 0.05 223.71% 1.12e-01

Compare Variance f[X]

No Variance f[X] values to compare.

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