:orphan: 





.. _pa_gen_pa_fit_badvar_fit:



Mixed error model fitted to mixed error data, but with incorrect variance definition
####################################################################################

[Generated automatically as a Fitting summary]

Inputs
******



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

:Name: pa_gen_pa_fit_badvar

:Title: Mixed error model fitted to mixed error data, but with incorrect variance definition

:Author: Wright Dose Ltd

:Abstract: 

| One compartment model with a depot leading to a central compartment
| This model contains both proportional and additive error, but erroneously sums the standard deviations.

:Keywords: one compartment model; dep_one_cmp_cl; proportional and additive error

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

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

:Diagram: 


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


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

.. code-block:: pyml

    f[PNOISE_STD] = 0.5
    f[ANOISE_STD] = 0.25



Outputs
*******



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

.. code-block:: pyml

    -396.750814736


which required 5 iterations and took 0.39 seconds

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

.. code-block:: pyml

    f[PNOISE_STD] = 0.069974
    f[ANOISE_STD] = 0.040035



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


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

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

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

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

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



Plots
*****



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



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


Alternatively see :ref:`pa_gen_pa_fit_badvar_dense_sim_plots`

Comparison
**********



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




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


===============  ==============  ================  =============  ============
Variable Name      Fitted Value    Starting Value    Prop Change    Abs Change
===============  ==============  ================  =============  ============
f[PNOISE_STD]         0.0699739              0.5        0.860052      0.430026
f[ANOISE_STD]         0.0400346              0.25       0.839862      0.209965
===============  ==============  ================  =============  ============

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


