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One Compartment Model with Absorption and no inter-occasion Variance f[CL_iov]=0

[Generated automatically as a Tutorial summary]

Inputs

Description

Name:d1cmp_cl_iov_naive
Title:One Compartment Model with Absorption and no inter-occasion Variance f[CL_iov]=0
Author:Wright Dose Ltd
Abstract:
Population one Compartment Model with Absorption and Inter-occasion Variance
Here f[CL_iov] is not estimated it is set to zero.
Keywords:one compartment model; dep_one_cmp_cl; iov
Input Script:d1cmp_cl_iov_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
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] = 0.0000

Outputs

Fitted f[X] values

f[KA] = 0.3201
f[CL] = 2.5351
f[V] = 20.9743
f[PNOISE_STD] = 0.2297
f[ANOISE_STD] = 0.0976
f[CL_isv] = 0.1395
f[CL_iov] = 0.0000

Plots

Dense comp plots

Alternatively see All dense_comp graph plots

Comparison

True objective value

-43.9474

Final fitted objective value

-253.7337

Compare Main f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[KA] 0.5 0.32 0.3 6.71% 2.01e-02
f[CL] 1 2.54 3 15.50% 4.65e-01
f[V] 15 21 20 4.87% 9.74e-01

Compare Noise f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[PNOISE_STD] 0.2 0.23 0.1 129.70% 1.30e-01
f[ANOISE_STD] 0.2 0.0976 0.05 95.10% 4.76e-02

Compare Variance f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[CL_isv] 0.01 0.14 0.2 30.23% 6.05e-02
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