:orphan: 





.. _emax_complex_tut:



Complex Emax PD Model
#####################

[Generated automatically as a Tutorial summary]

Model Description
*****************


:Name: emax_complex

:Title: Complex Emax PD Model

:Author: PoPy for PK/PD

:Abstract: 

| An complex emax PK/PD Model, based on the concentration of drug in the body.
| The two compartment PK model uses previously estimated values of CL, V1, Q and V2 for each individual
| The concentration in the central compartment influences the effect compartment along with EMAX (the maximum effect), EC50 (the concentration at which the effect is half the maximum) using a hill equation.

:Keywords: pkpd

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

:Diagram: 


.. thumbnail:: compartment_diagram.svg
    :width: 200px


Comparison
**********



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


.. code-block:: pyml

    305.2694



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


.. code-block:: pyml

    301.5421



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.

Outputs
*******



Fitted f[X] values (after fitting)
==================================


.. code-block:: pyml

    f[EMAX] = 105.0956
    f[E50] = 47.6442
    f[GAMMA] = 0.4755
    f[ANOISE] = 2.7512



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


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


Gen and Fit Summaries
=====================


* Gen: :ref:`emax_complex_gen` (gen)
* Fit: :ref:`emax_complex_fit` (fit)

Inputs
******



True f[X] values (for simulation)
=================================

.. code-block:: pyml

    f[EMAX] = 80.0000
    f[E50] = 20.0000
    f[GAMMA] = 0.5000
    f[ANOISE] = 3.0000



Starting f[X] values (before fitting)
=====================================

.. code-block:: pyml

    f[EMAX] = 100.0000
    f[E50] = 10.0000
    f[GAMMA] = 1.0000
    f[ANOISE] = 5.0000

