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isaacslavitt.com | ||
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austinrochford.com
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| | | | | Splines are a powerful tool when modeling nonlinear relationships. This post shows how to include splines in a Bayesian model in Python using pymc3. In addition, we will show how to use a second splin | |
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bambinos.github.io
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www.djmannion.net
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| | | | | Data are sometimes on a circular scale, such as the angle of an oriented stimulus, and the analysis of such data often needs to take this circularity into account. Here, we will look at how we can use PyMC to fit a model to circular data. | |
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jaketae.github.io
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| | | So far on this blog, we have looked the mathematics behind distributions, most notably binomial, Poisson, and Gamma, with a little bit of exponential. These distributions are interesting in and of themselves, but their true beauty shines through when we analyze them under the light of Bayesian inference. In today's post, we first develop an intuition for conditional probabilities to derive Bayes' theorem. From there, we motivate the method of Bayesian inference as a means of understanding probability. | ||
