:orphan: 





.. _blq_pk_fit:



Depot + One compartment PK with BLQ
###################################

[Generated automatically as a Fitting summary]

Inputs
******



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

:Name: blq_pk

:Title: Depot + One compartment PK with BLQ

:Author: J.R. Hartley

:Abstract: 

| Depot One Comp PK model, with BLQ (below level of quantification) observations.

:Keywords: tutorial; pk; advan4; dep_two_cmp; blq

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

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

:Diagram: 


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


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

.. code-block:: pyml

    f[KA] = 1.0000
    f[CL] = 1.0000
    f[V1] = 20.0000
    f[KA_isv,CL_isv,V1_isv] = [
        [ 0.0500, 0.0100, 0.0100 ],
        [ 0.0100, 0.0500, 0.0100 ],
        [ 0.0100, 0.0100, 0.0500 ],
    ]
    f[PNOISE] = 0.1000
    f[ANOISE] = 0.0100



Outputs
*******



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

.. code-block:: pyml

    -740.9643


which required 1.28 iterations and took 1313.73 seconds

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

.. code-block:: pyml

    f[KA] = 0.1950
    f[CL] = 2.0509
    f[V1] = 48.4223
    f[KA_isv,CL_isv,V1_isv] = [
        [ 0.0137, 0.0118, -0.0107 ],
        [ 0.0118, 0.0221, 0.0270 ],
        [ -0.0107, 0.0270, 0.1372 ],
    ]
    f[PNOISE] = 0.1486
    f[ANOISE] = 0.0100



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


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

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

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

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

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



Plots
*****



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



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


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


.. thumbnail:: images/fit_dense/000003.svg
    :width: 200px


Alternatively see :ref:`blq_pk_dense_sim_plots`

Comparison
**********



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


===============  ================  ==============  =============  ============
Variable Name      Starting Value    Fitted Value    Prop Change    Abs Change
===============  ================  ==============  =============  ============
f[KA]                      1.0000          0.1950         0.8050        0.8050
f[CL]                      1.0000          2.0509         1.0509        1.0509
f[V1]                     20.0000         48.4223         1.4211       28.4223
===============  ================  ==============  =============  ============

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


===============  ================  ==============  =============  ============
Variable Name      Starting Value    Fitted Value    Prop Change    Abs Change
===============  ================  ==============  =============  ============
f[PNOISE]                  0.1000          0.1486         0.4860        0.0486
===============  ================  ==============  =============  ============

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


================  ================  ==============  =============  ============
Variable Name       Starting Value    Fitted Value    Prop Change    Abs Change
================  ================  ==============  =============  ============
f[KA_isv]                   0.0500          0.0137         0.7257        0.0363
f[KA_isv;CL_isv]            0.0100          0.0118         0.1803        0.0018
f[KA_isv;V1_isv]            0.0100         -0.0107         2.0729        0.0207
f[CL_isv;KA_isv]            0.0100          0.0118         0.1803        0.0018
f[CL_isv]                   0.0500          0.0221         0.5578        0.0279
f[CL_isv;V1_isv]            0.0100          0.0270         1.6991        0.0170
f[V1_isv;KA_isv]            0.0100         -0.0107         2.0729        0.0207
f[V1_isv;CL_isv]            0.0100          0.0270         1.6991        0.0170
f[V1_isv]                   0.0500          0.1372         1.7435        0.0872
================  ================  ==============  =============  ============