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| -rw-r--r-- | gnu/packages/cran.scm | 33 |
1 files changed, 33 insertions, 0 deletions
diff --git a/gnu/packages/cran.scm b/gnu/packages/cran.scm index 852d536c5e..590e7008ee 100644 --- a/gnu/packages/cran.scm +++ b/gnu/packages/cran.scm @@ -28136,6 +28136,39 @@ estimation in measurement error models: The R package decon. Journal of Statistical Software, 39(10), 1-24.") (license license:gpl3+))) +(define-public r-densestbayes + (package + (name "r-densestbayes") + (version "1.0-2") + (source + (origin + (method url-fetch) + (uri (cran-uri "densEstBayes" version)) + (sha256 + (base32 "16fb7vkic9q5p8s4f0f215zmb36fcizqr4r2vm9dxxj9rasrg2f3")))) + (properties `((upstream-name . "densEstBayes"))) + (build-system r-build-system) + (propagated-inputs + (list r-bh + r-mass + r-nlme + r-rcpp + r-rcpparmadillo + r-rcppeigen + r-rcppparallel + r-rstan + r-rstantools + r-stanheaders)) + (home-page "https://cran.r-project.org/package=densEstBayes") + (synopsis "Density estimation via Bayesian inference engines") + (description + "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.") + (license license:gpl2+))) + (define-public r-locpol (package (name "r-locpol") |