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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:d1cmp_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:d1cmp_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

-394.5900

which required 1.22 iterations and took 550.23 seconds

Final fitted fixed effects

f[KA] = 0.3020
f[CL] = 3.2966
f[V] = 19.6506
f[PNOISE_STD] = 0.0712
f[ANOISE_STD] = 0.0545
f[CL_isv] = 0.1844

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 0.3020 0.3961 0.1980
f[CL] 1.0000 3.2966 2.2966 2.2966
f[V] 15.0000 19.6506 0.3100 4.6506

Compare Noise f[X]

Variable Name Starting Value Fitted Value Prop Change Abs Change
f[PNOISE_STD] 0.2000 0.0712 0.6439 0.1288
f[ANOISE_STD] 0.2000 0.0545 0.7276 0.1455

Compare Variance f[X]

Variable Name Starting Value Fitted Value Prop Change Abs Change
f[CL_isv] 0.0100 0.1844 17.4397 0.1744
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