:orphan: 





.. _circ_sin_fit:



Sine circadian model
####################

[Generated automatically as a Fitting summary]

Inputs
******



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

:Name: circ_sin

:Title: Sine circadian model

:Author: Wright Dose Ltd

:Abstract: 

| A PD Model based on the amount of drug in the body.
| The PD model uses a sine function which simulates a circadian rhythm for the generation of a biomarker.
| The amount in the central compartment is determined by CL and V, PK patameters , which have been previosly estimated for each individual.
| The amount in the central compartment influences the rate of production of a biomarker.

:Keywords: PD; Pharmacodynamics; sine function; Circadian rhythm

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

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

:Diagram: 


.. thumbnail:: circ_sin_fit.pyml_output/fit/compartment_diagram.svg
    :width: 200px


Initial fixed effect estimates
==============================

.. code-block:: pyml

    f[AMP] = 3.0000
    f[INT] = 16.0000
    f[KOUT] = 0.1000
    f[ANOISE] = 5.0000



Outputs
*******



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

.. code-block:: pyml

    1174.8667


which required N. iterations and took 2.52 seconds

Final fitted fixed effects
==========================

.. code-block:: pyml

    f[AMP] = 2.0061
    f[INT] = 19.8394
    f[KOUT] = 0.0501
    f[ANOISE] = 10.0000



Fitted parameter .csv files
===========================


:Fixed Effects: :download:`fx_params.csv (fit) <circ_sin_fit.pyml_output/fit/solN/fx_params.csv>`

:Random Effects: :download:`rx_params.csv (fit) <circ_sin_fit.pyml_output/fit/solN/rx_params.csv>`

:Model params: :download:`mx_params.csv (fit) <circ_sin_fit.pyml_output/fit/solN/mx_params.csv>`

:State values: :download:`sx_params.csv (fit) <circ_sin_fit.pyml_output/fit/solN/sx_params.csv>`

:Predictions: :download:`px_params.csv (fit) <circ_sin_fit.pyml_output/fit/solN/px_params.csv>`



Plots
*****



Dense sim plots
===============



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


Alternatively see :ref:`circ_sin_dense_sim_plots`

Comparison
**********



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


===============  ==============  ================  =============  ============
Variable Name      Fitted Value    Starting Value    Prop Change    Abs Change
===============  ==============  ================  =============  ============
f[AMP]                   2.0061            3.0000         0.3313        0.9939
f[INT]                  19.8394           16.0000         0.2400        3.8394
f[KOUT]                  0.0501            0.1000         0.4988        0.0499
===============  ==============  ================  =============  ============

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


===============  ==============  ================  =============  ============
Variable Name      Fitted Value    Starting Value    Prop Change    Abs Change
===============  ==============  ================  =============  ============
f[ANOISE]               10.0000            5.0000         1.0000        5.0000
===============  ==============  ================  =============  ============

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


