Additive error model fitted to proportional + additive noise synthetic data.

[Generated automatically as a Fitting summary]

Inputs

Description

Name:pa_gen_ao_fit Title:Additive error model fitted to proportional + additive noise synthetic data. Author:Wright Dose Ltd Abstract:

One compartment model with a depot leading to a central compartment.

This model contains both additive error only. Synthetic input data contain proportional and additive noise.

Keywords:one compartment model; dep_one_cmp_cl; additive error Input Script:pa_gen_ao_fit.pyml Input Data:synthetic_data.csv Diagram:

Initial fixed effect estimates

f[ANOISE_STD] = 0.2500

Outputs

Final objective value

-327.7085

which required 1.6 iterations and took 0.50 seconds

Final fitted fixed effects

f[ANOISE_STD] = 0.1178

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	Starting Value	Fitted Value	Prop Change	Abs Change
f[ANOISE_STD]	0.2500	0.1178	0.5287	0.1322

Compare Variance f[X]