: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
    f[INT] = 16
    f[KOUT] = 0.1
    f[ANOISE] = 5



Outputs
*******



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

.. code-block:: pyml

    812.580774422


which required N. iterations and took 907.43 seconds

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

.. code-block:: pyml

    f[AMP] = 1.9959
    f[INT] = 19.845
    f[KOUT] = 0.049823
    f[ANOISE] = 2.9042



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/000000.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]                1.99585                 3         0.334716     1.00415
f[INT]               19.845                  16         0.240312     3.84499
f[KOUT]               0.0498227               0.1       0.501773     0.0501773
===============  ==============  ================  =============  ============

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


===============  ==============  ================  =============  ============
Variable Name      Fitted Value    Starting Value    Prop Change    Abs Change
===============  ==============  ================  =============  ============
f[ANOISE]               2.90424                 5       0.419152       2.09576
===============  ==============  ================  =============  ============

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


