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Model containing both proportional and additive error

[Generated automatically as a Fitting summary]

Inputs

Description

Name:pa_gen_pa_fit
Title:Model containing both proportional and additive error
Author:Wright Dose Ltd
Abstract:
One compartment model with a depot leading to a central compartment.
This model contains both proportional and additive error.
Keywords:one compartment model; one_two_cmp_cl; proportional and additive error
Input Script:pa_gen_pa_fit_fit.pyml
Input Data:synthetic_data.csv
Diagram:

Initial fixed effect estimates

f[PNOISE_STD] = 0.5
f[ANOISE_STD] = 0.25

Outputs

Final objective value

-396.659750362

which required N. iterations and took 207.35 seconds

Final fitted fixed effects

f[PNOISE_STD] = 0.095119
f[ANOISE_STD] = 0.045335

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]

Compare Noise f[X]

Variable Name Fitted Value Starting Value Prop Change Abs Change
f[PNOISE_STD] 0.095119 0.5 0.809762 0.404881
f[ANOISE_STD] 0.0453351 0.25 0.81866 0.204665

Compare Variance f[X]

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