: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
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.. 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
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.. 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
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.. 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
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.. 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 `_