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 ckrapu.github.io
Don't know where your data is from? Bayesian modeling for unknown coordinates | Christopher Krapu
| | isaacslavitt.com
Isaac Slavitt: Solving the Bayesian German Tank problem with PyMC and PyStan
4.4 parsecs away

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| | [AI summary] The article discusses the German Tank Problem, a statistical estimation challenge where the goal is to infer the total number of tanks based on observed serial numbers, using Bayesian methods and MCMC libraries like Sampyl, PyMC3, and PyStan.
| | www.djmannion.net
Fitting models with circular data in PyMC
6.4 parsecs away

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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.
| | austinrochford.com
Bayesian Age/Period/Cohort Models in Python with PyMC | Austin Rochford
2.2 parsecs away

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| | For my day job, I spend a lot of time thinking about e-commerce analytics and cohort analysis in particular. Statistical age-period-cohort (APC) models are important in many fields such as epidemiolo
| | ggplot2.tidyverse.org
A box and whiskers plot (in the style of Tukey) - geom_boxplot ggplot2
29.0 parsecs away

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| The boxplot compactly displays the distribution of a continuous variable. It visualises five summary statistics (the median, two hinges and two whiskers), and all "outlying" points individually.