Language: en

Model containing both proportional and additive error¶

[Generated automatically as a Tutorial 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_tut.pyml`
Diagram:

True f[X] values¶

f[PNOISE_STD] = 0.1000
f[ANOISE_STD] = 0.0500

Starting f[X] values¶

f[PNOISE_STD] = 0.5000
f[ANOISE_STD] = 0.2500

Outputs¶

Generated data .csv file¶

Synthetic Data:	`synthetic_data.csv`

Generating and Fitting Summaries¶

Gen: Model containing both proportional and additive error (gen)
Fit: Model containing both proportional and additive error (fit)

Fitted f[X] values¶

f[PNOISE_STD] = 0.0951
f[ANOISE_STD] = 0.0453

Plots¶

Dense comp plots¶

Alternatively see All dense_comp graph plots

Comparison¶

True objective value¶

-395.5169

Final fitted objective value¶

-396.6598

Compare Main f[X]¶

No Main f[X] values to compare.

Compare Noise f[X]¶

Name	Initial	Fitted	True	Prop. Error	Abs. Error
f[PNOISE_STD]	0.5	0.0951	0.1	4.91%	4.91e-03
f[ANOISE_STD]	0.25	0.0453	0.05	9.36%	4.68e-03

Compare Variance f[X]¶

No Variance f[X] values to compare.

Documentation