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

[Generated automatically as a Fitting summary]

Inputs

Description

Name:dep_one_cmp_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:dep_one_cmp_cl_isv_fit.pyml
Input Data:synthetic_data.csv
Diagram:

Initial fixed effect estimates

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

Final objective value

-371.3278

which required 1.21 iterations and took 459.50 seconds

Final fitted fixed effects

f[KA] = 0.2643
f[CL] = 2.7416
f[V] = 19.1995
f[PNOISE_STD] = 0.1131
f[ANOISE_STD] = 0.0417
f[CL_isv] = 0.1648

Fitted parameter .csv files

Fixed Effects:fx_params.csv (fit)
Random Effects:rx_params.csv (fit)
Model params:mx_params.csv (fit)
State values:sx_params.csv (fit)
Predictions:px_params.csv (fit)

Plots

Dense sim plots

Alternatively see All dense_sim graph plots

Comparison

Compare Main f[X]

Variable Name Starting Value Fitted Value Prop Change Abs Change
f[KA] 0.5000 0.2643 0.4715 0.2357
f[CL] 1.0000 2.7416 1.7416 1.7416
f[V] 15.0000 19.1995 0.2800 4.1995

Compare Noise f[X]

Variable Name Starting Value Fitted Value Prop Change Abs Change
f[PNOISE_STD] 0.2000 0.1131 0.4345 0.0869
f[ANOISE_STD] 0.2000 0.0417 0.7916 0.1583

Compare Variance f[X]

Variable Name Starting Value Fitted Value Prop Change Abs Change
f[CL_isv] 0.0100 0.1648 15.4784 0.1548
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