• Language: en

One Compartment Model with Absorption and Inter-subject Variance f[CL_isv]=0.2

[Generated automatically as a Tutorial summary]

Inputs

Description

Name:d1cmp_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:d1cmp_cl_isv.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] = 0.0100

Outputs

Fitted f[X] values

f[KA] = 0.3019
f[CL] = 3.2984
f[V] = 19.6487
f[PNOISE_STD] = 0.0712
f[ANOISE_STD] = 0.0545
f[CL_isv] = 0.1843

Plots

Dense comp plots

Alternatively see All dense_comp graph plots

Comparison

True objective value

-389.4976

Final fitted objective value

-394.5899

Compare Main f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[KA] 0.5 0.302 0.3 0.64% 1.91e-03
f[CL] 1 3.3 3 9.95% 2.98e-01
f[V] 15 19.6 20 1.76% 3.51e-01

Compare Noise f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[PNOISE_STD] 0.2 0.0712 0.1 28.79% 2.88e-02
f[ANOISE_STD] 0.2 0.0545 0.05 8.96% 4.48e-03

Compare Variance f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[CL_isv] 0.01 0.184 0.2 7.84% 1.57e-02
Back to Top