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

[Generated automatically as a Tutorial summary]

Inputs

Description

Name:dep_one_cmp_cl_iov
Title:One Compartment Model with Absorption and Inter-occasion Variance f[CL_isv]=0.2
Author:Wright Dose Ltd
Abstract:
Population one Compartment Model with Absorption and Inter-occasion Variance
Keywords:one compartment model; dep_one_cmp_cl; iov
Input Script:dep_one_cmp_cl_iov.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
f[CL_iov] = 0.1000

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
f[CL_iov] = 0.0100

Outputs

Fitted f[X] values

f[KA] = 1.0000
f[CL] = 2.1808
f[V] = 19.7903
f[PNOISE_STD] = 0.2151
f[ANOISE_STD] = 0.0508
f[CL_isv] = 0.0741
f[CL_iov] = 0.1014

Plots

Dense comp plots

Alternatively see All dense_comp graph plots

Comparison

True objective value

-344.3934

Final fitted objective value

-275.4285

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 2.18 3 27.31% 8.19e-01
f[V] 15 19.8 20 1.05% 2.10e-01

Compare Noise f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[PNOISE_STD] 0.2 0.215 0.1 115.09% 1.15e-01
f[ANOISE_STD] 0.2 0.0508 0.05 1.55% 7.75e-04

Compare Variance f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[CL_isv] 0.01 0.0741 0.2 62.94% 1.26e-01
f[CL_iov] 0.01 0.101 0.1 1.39% 1.39e-03
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