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One Compartment Model with Absorption and Inter-occasion Variance f[CL_isv]=0.5

[Generated automatically as a Tutorial summary]

Inputs

Description

Name:d1cmp_cl_iov_05
Title:One Compartment Model with Absorption and Inter-occasion Variance f[CL_isv]=0.5
Author:Wright Dose Ltd
Abstract:
Population one Compartment Model with Absorption and Inter-occasion Variance
Here f[CL_isv] true value is 0.5
Keywords:one compartment model; dep_one_cmp_cl; iov
Input Script:d1cmp_cl_iov_05.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] = 0.5000
f[CL_iov] = 0.0100

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

Generated data .csv file

Synthetic Data:synthetic_data.csv

Fitted f[X] values

f[KA] = 0.3156
f[CL] = 2.3644
f[V] = 19.7231
f[PNOISE_STD] = 0.0984
f[ANOISE_STD] = 0.0486
f[CL_isv] = 0.3029
f[CL_iov] = 0.0029

Plots

Dense comp plots

Alternatively see All dense_comp graph plots

Comparison

True objective value

-375.4831

Final fitted objective value

-384.2726

Compare Main f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[KA] 0.5 0.316 0.3 5.18% 1.56e-02
f[CL] 1 2.36 3 21.19% 6.36e-01
f[V] 15 19.7 20 1.38% 2.77e-01

Compare Noise f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[PNOISE_STD] 0.2 0.0984 0.1 1.62% 1.62e-03
f[ANOISE_STD] 0.2 0.0486 0.05 2.76% 1.38e-03

Compare Variance f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[CL_isv] 0.01 0.303 0.5 39.43% 1.97e-01
f[CL_iov] 0.01 0.00291 0.01 70.94% 7.09e-03
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