:orphan: 





.. _d1cmp_cl_iov_naive_tut:



One Compartment Model with Absorption and no inter-occasion Variance f[CL_iov]=0
################################################################################

[Generated automatically as a Tutorial summary]

Inputs
******



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

:Name: d1cmp_cl_iov_naive

:Title: One Compartment Model with Absorption and no inter-occasion Variance f[CL_iov]=0

:Author: Wright Dose Ltd

:Abstract: 

| Population one Compartment Model with Absorption and Inter-occasion Variance
| Here f[CL_iov] is not estimated it is set to zero.

:Keywords: one compartment model; dep_one_cmp_cl; iov

:Input Script: :download:`d1cmp_cl_iov_naive.pyml <d1cmp_cl_iov_naive.pyml>`

:Diagram: 

Failed to create compartment diagram

True f[X] values
================

.. code-block:: pyml

    f[KA] = 0.3000
    f[CL] = 3.0000
    f[V] = 20.0000
    f[PNOISE_STD] = 0.1000
    f[ANOISE_STD] = 0.0500
    f[CL_isv] = 0.2000
    f[CL_iov] = 0.1000



Starting f[X] values
====================

.. code-block:: pyml

    f[KA] = 0.5000
    f[CL] = 1.0000
    f[V] = 15.0000
    f[PNOISE_STD] = 0.2000
    f[ANOISE_STD] = 0.2000
    f[CL_isv] = 0.0100
    f[CL_iov] = 0.0000



Outputs
*******



Generating and Fitting Summaries
================================

* Gen: :ref:`d1cmp_cl_iov_naive_gen` (gen)
* Fit: :ref:`d1cmp_cl_iov_naive_fit` (fit)

Fitted f[X] values
==================

.. code-block:: pyml

    f[KA] = 0.3201
    f[CL] = 2.5351
    f[V] = 20.9743
    f[PNOISE_STD] = 0.2297
    f[ANOISE_STD] = 0.0976
    f[CL_isv] = 0.1395
    f[CL_iov] = 0.0000



Plots
*****



Dense comp plots
================



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


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


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


Alternatively see :ref:`d1cmp_cl_iov_naive_dense_comp_plots`

Comparison
**********



True objective value
====================


.. code-block:: pyml

    -43.9474



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


.. code-block:: pyml

    -253.7337



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



.. csv-table:: 
    :file: fx_comp_main.csv
    :header-rows: 1


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



.. csv-table:: 
    :file: fx_comp_noise.csv
    :header-rows: 1


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



.. csv-table:: 
    :file: fx_comp_variance.csv
    :header-rows: 1
