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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:dep_one_cmp_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:dep_one_cmp_cl_isv_naive.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

Outputs

Fitted f[X] values

f[KA] = 1
f[CL] = 1
f[V] = 7.3224
f[PNOISE_STD] = 0.62876
f[ANOISE_STD] = 0.12415
f[CL_isv] = 0

Plots

Dense comp plots

Alternatively see All dense_comp graph plots

Comparison

True objective value

-362.687685887

Final fitted objective value

-60.4607888207

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 1 3 66.67% 2.00e+00
f[V] 15 7.32 20 63.39% 1.27e+01

Compare Noise f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[PNOISE_STD] 0.2 0.629 0.1 528.76% 5.29e-01
f[ANOISE_STD] 0.2 0.124 0.05 148.31% 7.42e-02

Compare Variance f[X]

No Variance f[X] values to compare.

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