:orphan: 





.. _biolag_abs_lag_tut:



Bioavailability and Lag
#######################

[Generated automatically as a Tutorial summary]

Inputs
******



Description
===========

:Name: biolag_abs_lag

:Title: Bioavailability and Lag

:Author: Wright Dose Ltd

:Abstract: 

| One compartment model absorption dosing with bioavailability and lag parameters.

:Keywords: identifiability; bioavailability; lag; dep_one_cmp_cl

:Input Script: :download:`biolag_abs_lag_tut.pyml <biolag_abs_lag_tut.pyml>`

:Diagram: 


.. thumbnail:: compartment_diagram.pdf
    :width: 200px


True f[X] values
================

.. code-block:: pyml

    f[KA] = 0.3000
    f[CL] = 3.0000
    f[V] = 20.0000
    f[ANOISE_STD] = 1.0000
    f[BIO] = 1.0000
    f[LAG] = 5.0000



Starting f[X] values
====================

.. code-block:: pyml

    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
*******



Generated data .csv file
========================


:Synthetic Data: :download:`synthetic_data.csv <synthetic_data.csv>`


Generating and Fitting Summaries
================================

* Gen: :ref:`biolag_abs_lag_gen` (gen)
* Fit: :ref:`biolag_abs_lag_fit` (fit)

Fitted f[X] values
==================

.. code-block:: pyml

    f[KA] = 0.9911
    f[CL] = 0.8428
    f[V] = 5.9136
    f[ANOISE_STD] = 0.8909
    f[BIO] = 0.2622
    f[LAG] = 8.6494



Plots
*****



Dense comp plots
================



.. thumbnail:: images/comp_dense/000001.svg
    :width: 200px


Alternatively see :ref:`biolag_abs_lag_dense_comp_plots`

Comparison
**********



True objective value
====================


.. code-block:: pyml

    44.2050



Final fitted objective value
============================


.. code-block:: pyml

    38.5365



Compare Main f[X]
=================



.. csv-table:: 
    :file: fx_comp_main.csv
    :header-rows: 1


Compare Noise f[X]
==================



.. csv-table:: 
    :file: fx_comp_noise.csv
    :header-rows: 1


Compare Variance f[X]
=====================


No Variance f[X] values to compare.