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

memory

Some initial concepts to get into head are the differences between:

  • bayesian probability
  • bayesian statistics
  • bayesian inference

Wider thoughts on application

the wider applications

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

My paper

my paper

https://christopherpaine.github.io/bayesian-ifoa/
https://vle.actuaries.org.uk/course/view.php?id=2709

«insert egress link»


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