:orphan:
Maximum Likelihood Estimation Examples
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
These notebooks illustrate the use of the Inference Model alternatives to create a model for inference, and the MLE class to perform maximum likelihood estimation of the parameters of that model. Recall that a maximum likelihood estimate is simply the parameter vector that maximizes the likelihood:
.. math:: \theta_{ML} = argmax_{\theta} \quad p(data \vert \theta)
.. raw:: html
.. raw:: html
.. only:: html
.. image:: /auto_examples/inference/mle/images/thumb/sphx_glr_regression_model_thumb.png
:alt:
:ref:`sphx_glr_auto_examples_inference_mle_regression_model.py`
.. raw:: html
Regression model
.. raw:: html
.. only:: html
.. image:: /auto_examples/inference/mle/images/thumb/sphx_glr_plot_learn_distribution_model_thumb.png
:alt:
:ref:`sphx_glr_auto_examples_inference_mle_plot_learn_distribution_model.py`
.. raw:: html
Simple probability distribution model
.. raw:: html
.. only:: html
.. image:: /auto_examples/inference/mle/images/thumb/sphx_glr_plot_complex_probability_model_thumb.png
:alt:
:ref:`sphx_glr_auto_examples_inference_mle_plot_complex_probability_model.py`
.. raw:: html
Complex probability distribution model
.. raw:: html
.. toctree::
:hidden:
/auto_examples/inference/mle/regression_model
/auto_examples/inference/mle/plot_learn_distribution_model
/auto_examples/inference/mle/plot_complex_probability_model
.. only:: html
.. container:: sphx-glr-footer sphx-glr-footer-gallery
.. container:: sphx-glr-download sphx-glr-download-python
:download:`Download all examples in Python source code: mle_python.zip `
.. container:: sphx-glr-download sphx-glr-download-jupyter
:download:`Download all examples in Jupyter notebooks: mle_jupyter.zip `
.. only:: html
.. rst-class:: sphx-glr-signature
`Gallery generated by Sphinx-Gallery