# Model containing proportional error only, with proportional only data

[Generated automatically as a Tutorial summary]

## Model Description

Name:

  po_gen_po_fit

Title:

  Model containing proportional error only, with proportional only data

Author:

  PoPy for PK/PD

Abstract:

One compartment model with a depot leading to a central compartment.
This model contains proportional error and no additive error. The synthetic input data contains only proportional error too.

Keywords:

  one compartment model; dep_one_cmp_cl; proportional error

Input Script:

  `po_tut.pyml`

Diagram:

## Comparison

### True objective value

    -571.8694

### Final fitted objective value

    -572.8210

### Compare Main f[X]

No Main f[X] values to compare.

### Compare Noise f[X]

Name | Initial | Fitted | True | Abs. Error | Prop. Error
--- | --- | --- | --- | --- | ---
f[PNOISE_STD] | 0.5 | 0.0932 | 0.1 | 6.82e-03 | 6.82%

### Compare Variance f[X]

No Variance f[X] values to compare.

## Outputs

### Fitted f[X] values (after fitting)

    f[PNOISE_STD] = 0.0932

### Generated data .csv file

Synthetic Data:

  `synthetic_data.csv`

### Gen and Fit Summaries

- Gen: Model containing proportional error only, with proportional only data (gen)

- Fit: Model containing proportional error only, with proportional only data (fit)

## Inputs

### True f[X] values (for simulation)

    f[PNOISE_STD] = 0.1000

### Starting f[X] values (before fitting)

    f[PNOISE_STD] = 0.5000