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author | Ricardo Wurmus <rekado@elephly.net> | 2019-03-12 22:12:44 +0100 |
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committer | Ricardo Wurmus <rekado@elephly.net> | 2019-03-12 22:47:56 +0100 |
commit | 8cd3f49d464935d2b266de112aa4b69e7609fae0 (patch) | |
tree | 559d230eef4bc33de3c6265ecac9b6eedaf580de /gnu/packages/cran.scm | |
parent | 1901a53241708f64a4c97df5f12c6412a49e697a (diff) | |
download | patches-8cd3f49d464935d2b266de112aa4b69e7609fae0.tar patches-8cd3f49d464935d2b266de112aa4b69e7609fae0.tar.gz |
gnu: Add r-bayesm.
* gnu/packages/cran.scm (r-bayesm): New variable.
Diffstat (limited to 'gnu/packages/cran.scm')
-rw-r--r-- | gnu/packages/cran.scm | 35 |
1 files changed, 35 insertions, 0 deletions
diff --git a/gnu/packages/cran.scm b/gnu/packages/cran.scm index 7a49beee4e..877ddea19b 100644 --- a/gnu/packages/cran.scm +++ b/gnu/packages/cran.scm @@ -10941,3 +10941,38 @@ several common set, element and attribute related tasks.") "This package provides a collection of some tests commonly used for identifying outliers.") (license license:gpl2+))) + +(define-public r-bayesm + (package + (name "r-bayesm") + (version "3.1-1") + (source + (origin + (method url-fetch) + (uri (cran-uri "bayesm" version)) + (sha256 + (base32 + "0y30cza92s6kgvmxjpr6f5g0qbcck7hslqp89ncprarhxiym2m28")))) + (build-system r-build-system) + (propagated-inputs + `(("r-rcpp" ,r-rcpp) + ("r-rcpparmadillo" ,r-rcpparmadillo))) + (home-page "http://www.perossi.org/home/bsm-1") + (synopsis "Bayesian inference for marketing/micro-econometrics") + (description + "This package covers many important models used in marketing and +micro-econometrics applications, including Bayes Regression (univariate or +multivariate dep var), Bayes Seemingly Unrelated Regression (SUR), Binary and +Ordinal Probit, Multinomial Logit (MNL) and Multinomial Probit (MNP), +Multivariate Probit, Negative Binomial (Poisson) Regression, Multivariate +Mixtures of Normals (including clustering), Dirichlet Process Prior Density +Estimation with normal base, Hierarchical Linear Models with normal prior and +covariates, Hierarchical Linear Models with a mixture of normals prior and +covariates, Hierarchical Multinomial Logits with a mixture of normals prior +and covariates, Hierarchical Multinomial Logits with a Dirichlet Process prior +and covariates, Hierarchical Negative Binomial Regression Models, Bayesian +analysis of choice-based conjoint data, Bayesian treatment of linear +instrumental variables models, Analysis of Multivariate Ordinal survey data +with scale usage heterogeneity, and Bayesian Analysis of Aggregate Random +Coefficient Logit Models.") + (license license:gpl2+))) |