# 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] = 0.5000
    f[CL] = 1.0000
    f[V] = 15.0000
    f[ANOISE_STD] = 5.0000
    f[BIO] = 0.8000
    f[LAG] = 1.0000

## Outputs

### Final objective value

    38.7523

which required N. iterations and took 1.21 seconds

### Final fitted fixed effects

    f[KA] = 1.0000
    f[CL] = 1.4961
    f[V] = 9.1492
    f[ANOISE_STD] = 0.8936
    f[BIO] = 0.2861
    f[LAG] = 8.9095

### 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] | 1.0000 | 0.5000 | 1.0000 | 0.5000
f[CL] | 1.4961 | 1.0000 | 0.4961 | 0.4961
f[V] | 9.1492 | 15.0000 | 0.3901 | 5.8508
f[BIO] | 0.2861 | 0.8000 | 0.6423 | 0.5139
f[LAG] | 8.9095 | 1.0000 | 7.9095 | 7.9095

### Compare Noise f[X]

Variable Name | Fitted Value | Starting Value | Prop Change | Abs Change
--- | --- | --- | --- | ---
f[ANOISE_STD] | 0.8936 | 5.0000 | 0.8213 | 4.1064

### Compare Variance f[X]