:orphan: 





.. _fit_example1_fit:



Simple Fit Example
##################

[Generated automatically as a Fitting summary]

Inputs
******



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

:Name: fit_example1

:Title: Simple Fit Example

:Author: J.R. Hartley

:Abstract: 

| One compartment model with elimination rate constant KE.

:Keywords: one compartment model; iv_one_cmp_k

:Input Script: :download:`fit_example1.pyml <fit_example1.pyml>`

:Input Data: :download:`fit_example1_data.csv <fit_example1_data.csv>`

:Diagram: 


.. thumbnail:: fit_example1.pyml_output/fit/compartment_diagram.svg
    :width: 200px


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

.. code-block:: pyml

    f[KE] = 0.05
    f[PNOISE] = 0.1
    f[KE_isv] = 0.1



Outputs
*******



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

.. code-block:: pyml

    303.073646611


which required 9 iterations and took 8.41 seconds

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

.. code-block:: pyml

    f[KE] = 0.096943
    f[PNOISE] = 0.21712
    f[KE_isv] = 0.01684



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


:Fixed Effects: :download:`fx_params.csv (fit) <fit_example1.pyml_output/fit/solN/fx_params.csv>`

:Random Effects: :download:`rx_params.csv (fit) <fit_example1.pyml_output/fit/solN/rx_params.csv>`

:Model params: :download:`mx_params.csv (fit) <fit_example1.pyml_output/fit/solN/mx_params.csv>`

:State values: :download:`sx_params.csv (fit) <fit_example1.pyml_output/fit/solN/sx_params.csv>`

:Predictions: :download:`px_params.csv (fit) <fit_example1.pyml_output/fit/solN/px_params.csv>`



Plots
*****



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



.. thumbnail:: images/fit_dense/000000.svg
    :width: 200px


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


.. thumbnail:: images/fit_dense/000002.svg
    :width: 200px


Alternatively see :ref:`fit_example1_dense_sim_plots`

Comparison
**********



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


===============  ==============  ================  =============  ============
Variable Name      Fitted Value    Starting Value    Prop Change    Abs Change
===============  ==============  ================  =============  ============
f[KE]                 0.0969428              0.05       0.938855     0.0469428
===============  ==============  ================  =============  ============

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


===============  ==============  ================  =============  ============
Variable Name      Fitted Value    Starting Value    Prop Change    Abs Change
===============  ==============  ================  =============  ============
f[PNOISE]              0.217116               0.1        1.17116      0.117116
===============  ==============  ================  =============  ============

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


===============  ==============  ================  =============  ============
Variable Name      Fitted Value    Starting Value    Prop Change    Abs Change
===============  ==============  ================  =============  ============
f[KE_isv]             0.0168404               0.1       0.831596     0.0831596
===============  ==============  ================  =============  ============