# Bioavailability and Lag

[Generated automatically as a Fitting summary]

## Inputs

### Description

Name: | biolag_abs_both
Title: | Bioavailability and Lag
Author: | Wright Dose Ltd
Abstract: |

One compartment model absorption dosing with bioavailability and lag parameters.

Keywords: | identifiability; bioavailability; lag
Input Script: | `biolag_abs_both_fit.pyml`
Input Data: | `synthetic_data.csv`
Diagram: |

### Initial fixed effect estimates

    f[KA] = 0.5
    f[CL] = 1
    f[V] = 15
    f[ANOISE_STD] = 5
    f[BIO] = 1
    f[LAG] = 1

## Outputs

### Final objective value

    39.6942478039

which required 7 iterations and took 0.55 seconds

### Final fitted fixed effects

    f[KA] = 0.97089
    f[CL] = 1.6898
    f[V] = 13.526
    f[ANOISE_STD] = 0.90185
    f[BIO] = 1
    f[LAG] = 0.00049507

### 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]

Variable Name | Fitted Value | Starting Value | Prop Change | Abs Change
--- | --- | --- | --- | ---
f[KA] | 0.970889 | 0.5 | 0.941777 | 0.470889
f[CL] | 1.68982 | 1 | 0.68982 | 0.68982
f[V] | 13.5257 | 15 | 0.0982881 | 1.47432
f[BIO] | 1 | 1 | 0 | 0
f[LAG] | 0.000495075 | 1 | 0.999505 | 0.999505

### Compare Noise f[X]

Variable Name | Fitted Value | Starting Value | Prop Change | Abs Change
--- | --- | --- | --- | ---
f[ANOISE_STD] | 0.901855 | 5 | 0.819629 | 4.09815

### Compare Variance f[X]