: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

    811.9734


which required 1.24 iterations and took 14.40 seconds

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

.. code-block:: pyml

    f[AMP] = 2.0055
    f[INT] = 7.8725
    f[KOUT] = 0.0501
    f[ANOISE] = 3.0838



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      Starting Value    Fitted Value    Prop Change    Abs Change
===============  ================  ==============  =============  ============
f[AMP]                     3.0000          2.0055         0.3315        0.9945
f[INT]                    16.0000          7.8725         0.5080        8.1275
f[KOUT]                    0.1000          0.0501         0.4989        0.0499
===============  ================  ==============  =============  ============

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


===============  ================  ==============  =============  ============
Variable Name      Starting Value    Fitted Value    Prop Change    Abs Change
===============  ================  ==============  =============  ============
f[ANOISE]                  5.0000          3.0838         0.3832        1.9162
===============  ================  ==============  =============  ============

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


