Merge pull request #24794 from SulphurFH/add-r-bvar

add-r-bvar

recipes/r-bvar/bld.bat

@@ -0,0 +1,2 @@
+"%R%" CMD INSTALL --build . %R_ARGS%
+IF %ERRORLEVEL% NEQ 0 exit /B 1

recipes/r-bvar/build.sh

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+#!/bin/bash
+export DISABLE_AUTOBREW=1
+${R} CMD INSTALL --build . ${R_ARGS}

recipes/r-bvar/meta.yaml

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+{% set version = '1.0.4' %}
+{% set posix = 'm2-' if win else '' %}
+{% set native = 'm2w64-' if win else '' %}
+
+package:
+  name: r-bvar
+  version: {{ version|replace("-", "_") }}
+
+source:
+  url:
+    - {{ cran_mirror }}/src/contrib/BVAR_{{ version }}.tar.gz
+    - {{ cran_mirror }}/src/contrib/Archive/BVAR/BVAR_{{ version }}.tar.gz
+  sha256: 440ce37924187183dd54e7e0f6ebf8e5faf52b1fbaac6914cca3f0c6bcc56b89
+
+build:
+  merge_build_host: True  # [win]
+  number: 0
+  noarch: generic
+  rpaths:
+    - lib/R/lib/
+    - lib/
+
+requirements:
+  build:
+    - {{ posix }}zip               # [win]
+    - cross-r-base {{ r_base }}    # [build_platform != target_platform]
+  host:
+    - r-base
+    - r-mvtnorm
+  run:
+    - r-base
+    - r-mvtnorm
+
+test:
+  commands:
+    - $R -e "library('BVAR')"           # [not win]
+    - "\"%R%\" -e \"library('BVAR')\""  # [win]
+
+about:
+  home: https://github.com/nk027/bvar
+  license: GPL-3.0-only
+  summary: Estimation of hierarchical Bayesian vector autoregressive models following Kuschnig
+    & Vashold (2021) <doi:10.18637/jss.v100.i14>. Implements hierarchical prior selection
+    for conjugate priors in the fashion of Giannone, Lenza & Primiceri (2015) <doi:10.1162/REST_a_00483>.
+    Functions to compute and identify impulse responses, calculate forecasts, forecast
+    error variance decompositions and scenarios are available. Several methods to print,
+    plot and summarise results facilitate analysis.
+  license_family: GPL3
+  license_file:
+    - '{{ environ["PREFIX"] }}/lib/R/share/licenses/GPL-3'
+    - LICENSE
+
+extra:
+  recipe-maintainers:
+    - conda-forge/r
+    - SulphurFH
+
+# Package: BVAR
+# Type: Package
+# Title: Hierarchical Bayesian Vector Autoregression
+# Version: 1.0.4
+# Date: 2023-03-08
+# Authors@R: c(person("Nikolas", "Kuschnig", role = c("aut", "cre"), email = "[email protected]", comment = c(ORCID = "0000-0002-6642-2543")), person("Lukas", "Vashold", role = "aut", comment = c(ORCID = "0000-0002-3562-3414")), person("Nirai", "Tomass", role = "ctb"), person("Michael", "McCracken", role = "dtc"), person("Serena", "Ng", role = "dtc"))
+# Author: Nikolas Kuschnig [aut, cre] (<https://orcid.org/0000-0002-6642-2543>), Lukas Vashold [aut] (<https://orcid.org/0000-0002-3562-3414>), Nirai Tomass [ctb], Michael McCracken [dtc], Serena Ng [dtc]
+# Maintainer: Nikolas Kuschnig <[email protected]>
+# Description: Estimation of hierarchical Bayesian vector autoregressive models following Kuschnig & Vashold (2021) <doi:10.18637/jss.v100.i14>. Implements hierarchical prior selection for conjugate priors in the fashion of Giannone, Lenza & Primiceri (2015) <doi:10.1162/REST_a_00483>. Functions to compute and identify impulse responses, calculate forecasts, forecast error variance decompositions and scenarios are available. Several methods to print, plot and summarise results facilitate analysis.
+# URL: https://github.com/nk027/bvar
+# BugReports: https://github.com/nk027/bvar/issues
+# Depends: R (>= 3.3.0)
+# Imports: mvtnorm, stats, graphics, utils, grDevices
+# Suggests: coda, vars, tinytest
+# License: GPL-3 | file LICENSE
+# Encoding: UTF-8
+# LazyData: true
+# RoxygenNote: 7.2.3
+# NeedsCompilation: no
+# Packaged: 2023-03-08 18:37:16 UTC; nikolas
+# Repository: CRAN
+# Date/Publication: 2023-03-08 19:30:06 UTC