# Model containing proportional error only, with proportional only data

[Generated automatically as a Tutorial summary]

## Inputs

### Description

Name: | po_gen_po_fit
Title: | Model containing proportional error only, with proportional only data
Author: | Wright Dose Ltd
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: |

### True f[X] values

    f[PNOISE_STD] = 0.1000

### Starting f[X] values

    f[PNOISE_STD] = 0.5000

## Outputs

### Generated data .csv file

Synthetic Data: | `synthetic_data.csv`

### Generating and Fitting Summaries

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

### Fitted f[X] values

    f[PNOISE_STD] = 0.0928

## Plots

### Dense comp plots

Alternatively see All dense_comp graph plots

## Comparison

### True objective value

    -572.6714

### Final fitted objective value

    -573.7490

### 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 | 0.0928 | 0.1 | 7.25% | 7.25e-03

### Compare Variance f[X]

No Variance f[X] values to compare.