Bayesian Methods Working Party
Approach
The approach is 2 pronged:
- learn more about bayesians - to help with applications and implementation
- learn more about captial - to help with applications
subsequent to this you can work on your paper
the technology
i give description at github readme page
Grammar
Some initial concepts to get into head are the differences between:
- bayesian probability
- bayesian statistics
- bayesian inference
Wider thoughts on application
Classical statistics is not Bayesian statistics with a single prior
- bayesian statistics treats parameters as a random variable + updates prior distributions to get a posterior
- classical statistics treats parameters as fixed but unknown
does not having a prior mean paramter treated in classical way
- bayesian statistics always requires a prior
- you may want to consider non informative priors to minimise the influence on the posterior
Wider Reading
| Column 1 | brendan-brewer-paper.html |
|---|---|
| two-envelopes-problem | Row 2, Cell 2 |
My paper
Links
https://christopherpaine.github.io/bayesian-ifoa/
https://vle.actuaries.org.uk/course/view.php?id=2709
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