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scipy.github.io | ||
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667-per-cm.net
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| | | | | This post could also be subtitled "Residual deviance isn't the whole story." My favorite book on logistic regression is by Dr Joseph Hilbe, Logistic Regression Models, CRC Press, 2009, Chapman & Hill. It is a solidly frequentist text, but its discussion of models and rich examples make that besides the point. Except in one case.... | |
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darrenjw.wordpress.com
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| | | | | Yesterday there was an RSS Read Paper meeting for the paper Unbiased Markov chain Monte Carlo with couplings by Pierre Jacob, John O'Leary and Yves F. Atchadé. The paper addresses the bias in MCMC estimates due to lack of convergence to equilibrium (the "burn-in" problem), and shows how it is possible to modify MCMC algorithms... | |
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erikbern.com
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| | | | | I made a New Year's resolution: every plot I make during 2018 will contain uncertainty estimates. Nine months in and I have learned a lot, so I put together a summary of some of the most useful methods. | |
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gist.github.com
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| | | Implementing a Network-based Model of Epilepsy with Numpy and Numba. Code for https://danielegrattarola.github.io/posts/2019-10-03/epilepsy-model.html - eeg_generator_numba.py | ||
