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Hi Toby,
I am really impressed with your lecture slides for the course. šš¾ They are really thorough with just the right content which makes for amazing visuals. At first I thought they were made usiā¦
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ć»Read some papers and lecture notes
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Hey @rsullivan-lord,
I was able to get PyABC set up and working. It looks like it's able to get posteriors that make sense, which is good! Instead of predicting for the whole data set (i.e. 1980 toā¦
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I'm having an issue running the example from "Understanding empirical Bayesian hierarchical modeling (using baseball statistics)"
http://varianceexplained.org/r/hierarchical_bayes_baseball/
I run ā¦
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# Tweet summary
Total: 22 books (5956pages), 3 lecture (70hrs)
> Statistics: 14 books (3557pages), 1 lecture (5hrs)
> Bayes: 4 books (1447pages), 2 lecture (64hrs)
> Others (Algorithm,ā¦
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One idea for this module is to have a couple of parts:
1. Why were are not teaching stats
2. How do to good exploratory data analysis
For point 1., some things to say:
* Statistics is hard, ā¦
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This meta-issue is a roadmap for the developments of the `AggJoiner` and `AggTarget` estimators, currently implemented in #600.
We need to merge the following PRs before tackling any of the developā¦
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## š Feature
Implement the positive-definite-matrix-valued Wishart and inverse-Wishart distributions, currently missing from `torch.distributions`.
## Motivation
These distributions often popā¦
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I found this by chance
https://en.wikipedia.org/wiki/Quantile-parameterized_distribution
assumes bounded support of distribution
It doesn't look popular enough as serious user facing distributiā¦