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One Compartment Model with Absorption and no inter-subject Variance f[CL_isv]=0

[Generated automatically as a Fitting summary]

Inputs

Description

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

Outputs

Final objective value

-60.4607888206

which required N. iterations and took 364.79 seconds

Final fitted fixed effects

f[KA] = 1
f[CL] = 1
f[V] = 7.3224
f[PNOISE_STD] = 0.62876
f[ANOISE_STD] = 0.12415
f[CL_isv] = 0

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] 1 1 0 0
f[V] 7.32241 15 0.511839 7.67759

Compare Noise f[X]

Variable Name Fitted Value Starting Value Prop Change Abs Change
f[PNOISE_STD] 0.628762 0.2 2.14381 0.428762
f[ANOISE_STD] 0.124153 0.2 0.379233 0.0758466

Compare Variance f[X]

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