# Additive noise model fitted to proportional noise only synthetic data.

[Generated automatically as a Fitting summary]

## Inputs

### Description

Name: | po_gen_ao_fit
Title: | Additive noise model fitted to proportional noise only synthetic data.
Author: | Wright Dose Ltd
Abstract: |

One compartment model with a depot leading to a central compartment.
This model contains additive error only. The synthetic input data only contains additive noise too.

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

### Initial fixed effect estimates

    f[ANOISE_STD] = 0.25

## Outputs

### Final objective value

    -341.711532537

which required N. iterations and took 172.15 seconds

### Final fitted fixed effects

    f[ANOISE_STD] = 0.10999

### 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[ANOISE_STD] | 0.109991 | 0.25 | 0.560035 | 0.140009

### Compare Variance f[X]