# 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

    39.6881

which required N. iterations and took 0.93 seconds

### Final fitted fixed effects

    f[KA] = 1.0000
    f[CL] = 1.2315
    f[V] = 9.8743
    f[ANOISE_STD] = 0.9026
    f[BIO] = 0.6750
    f[LAG] = 0.6327

### 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] | 1.2315 | 1.0000 | 0.2315 | 0.2315
f[V] | 9.8743 | 15.0000 | 0.3417 | 5.1257
f[BIO] | 0.6750 | 0.8000 | 0.1562 | 0.1250
f[LAG] | 0.6327 | 1.0000 | 0.3673 | 0.3673

### Compare Noise f[X]

Variable Name | Fitted Value | Starting Value | Prop Change | Abs Change
--- | --- | --- | --- | ---
f[ANOISE_STD] | 0.9026 | 5.0000 | 0.8195 | 4.0974

### Compare Variance f[X]