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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] = 0.5
f[CL] = 1
f[V] = 15
f[PNOISE_STD] = 0.2
f[ANOISE_STD] = 0.2
f[CL_isv] = 0.01

Outputs

Final objective value

-311.996254196

which required 31 iterations and took 146.40 seconds

Final fitted fixed effects

f[KA] = 1
f[CL] = 2.4567
f[V] = 22.048
f[PNOISE_STD] = 0.23467
f[ANOISE_STD] = 0.03752
f[CL_isv] = 0.1284

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 Fitted Value Starting Value Prop Change Abs Change
f[KA] 1 0.5 1 0.5
f[CL] 2.45673 1 1.45673 1.45673
f[V] 22.0483 15 0.469884 7.04826

Compare Noise f[X]

Variable Name Fitted Value Starting Value Prop Change Abs Change
f[PNOISE_STD] 0.234672 0.2 0.173361 0.0346722
f[ANOISE_STD] 0.0375202 0.2 0.812399 0.16248

Compare Variance f[X]

Variable Name Fitted Value Starting Value Prop Change Abs Change
f[CL_isv] 0.128403 0.01 11.8403 0.118403
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