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Bayesian density estimates for univariate continuous random samples are provided using the Bayesian inference engine paradigm. The engine options are: Hamiltonian Monte Carlo, the no U-turn sampler, semiparametric mean field variational Bayes and slice sampling. The methodology is described in Wand and Yu (2020) <arXiv:2009.06182>.

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conda 2.4 MB | win-64/r-densestbayes-1.0_2-r40ha856d6a_0.tar.bz2  2 years and 9 months ago 700 main
conda 2.4 MB | win-64/r-densestbayes-1.0_2-r41ha856d6a_0.tar.bz2  2 years and 9 months ago 694 main
conda 2.5 MB | osx-64/r-densestbayes-1.0_2-r40hca8169d_0.tar.bz2  2 years and 9 months ago 74 main
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conda 2.5 MB | linux-64/r-densestbayes-1.0_2-r41hcec875b_0.tar.bz2  2 years and 9 months ago 2066 main
conda 2.5 MB | linux-64/r-densestbayes-1.0_2-r40hcec875b_0.tar.bz2  2 years and 9 months ago 2081 main

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