GitHub - idontgetoutmuch/HasBayes: Bayesian Analysis in Haskell

Branches Tags

Name		Name	Last commit message	Last commit date
Latest commit History 46 Commits
DataSciencePres		DataSciencePres
Jags		Jags
BEST.hs		BEST.hs
Bayes.bib		Bayes.bib
BernMetropolis.lhs		BernMetropolis.lhs
BernMetropolisTemplate.R		BernMetropolisTemplate.R
BernMetropolisTemplate.hs		BernMetropolisTemplate.hs
ConjMCMCSimple.lhs		ConjMCMCSimple.lhs
FuncBernMetropolis.R		FuncBernMetropolis.R
LinReg.lhs		LinReg.lhs
LinRegAux.hs		LinRegAux.hs
LinRegSingle.hs		LinRegSingle.hs
PopGrowthMCMC.lhs		PopGrowthMCMC.lhs
PopGrowthMCMCChart.hs		PopGrowthMCMCChart.hs
PopGrowthMCMCMain.hs		PopGrowthMCMCMain.hs
README		README
StudentAux.hs		StudentAux.hs
StudentTest.lhs		StudentTest.lhs
TestFu.hs		TestFu.hs

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This was going to be an EDSL in Haskell to Jags (after all there is no
need to re-invent the Gibbs sampler wheel) but the world has moved
on. First let us do some examples of Bayesian regression using
Hamiltonian Monte Carlo and then maybe we can think about interfacing
to STAN.