HTTP 200 OK
Allow: GET, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept
{
"count": 50429,
"next": "https://ports.macports.org/api/v1/ports/?format=api&ordering=created_at&page=757",
"previous": "https://ports.macports.org/api/v1/ports/?format=api&ordering=created_at&page=755",
"results": [
{
"name": "R-dr",
"portdir": "R/R-dr",
"version": "3.0.10",
"license": "(GPL-2 or GPL-3)",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://cran.r-project.org/package=dr",
"description": "Methods for dimension reduction for regression",
"long_description": "Methods for dimension reduction for regression",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"R",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"R-CRAN-recommended"
]
},
{
"type": "run",
"ports": [
"R"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"R-quantdr",
"R-orthoDr"
]
},
{
"type": "test",
"ports": [
"R-tsBSS"
]
}
]
},
{
"name": "R-echoice2",
"portdir": "R/R-echoice2",
"version": "0.2.4",
"license": "MIT",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "http://ninohardt.de/echoice2",
"description": "Choice models based on economic theory",
"long_description": "Choice models based on economic theory",
"active": true,
"categories": [
"science",
"math",
"R",
"economics"
],
"maintainers": [
{
"name": "vital.had",
"github": "barracuda156",
"ports_count": 2571
}
],
"variants": [
"clang10",
"clang11",
"clang12",
"clang13",
"clang14",
"clang15",
"clang16",
"clang50",
"clang60",
"clang70",
"clang80",
"clang90",
"clangdevel",
"g95",
"gcc10",
"gcc11",
"gcc12",
"gcc13",
"gccdevel",
"gfortran"
],
"dependencies": [
{
"type": "build",
"ports": [
"gcc13",
"R",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"R-magrittr",
"R-rlang",
"R-stringr",
"R-tibble",
"R-dplyr",
"R-purrr",
"R-tidyr",
"R-tidyselect",
"R-ggplot2",
"R-forcats",
"R-CRAN-recommended",
"libgcc",
"R-Rcpp",
"R-RcppArmadillo"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-bayesm",
"R-knitr",
"R-testthat",
"R-rmarkdown"
]
}
],
"depends_on": []
},
{
"name": "R-fpop",
"portdir": "R/R-fpop",
"version": "2019.08.26",
"license": "(LGPL-2.1 or LGPL-3)",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://cran.r-project.org/package=fpop",
"description": "Segmentation using optimal partitioning and function pruning",
"long_description": "Segmentation using optimal partitioning and function pruning",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"R",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"R-CRAN-recommended"
]
},
{
"type": "run",
"ports": [
"R"
]
}
],
"depends_on": [
{
"type": "test",
"ports": [
"R-crops",
"R-atime"
]
}
]
},
{
"name": "R-gamlr",
"portdir": "R/R-gamlr",
"version": "1.13-8",
"license": "GPL-3",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://cran.r-project.org/package=gamlr",
"description": "Gamma lasso regression",
"long_description": "Gamma lasso regression",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [
{
"name": "vital.had",
"github": "barracuda156",
"ports_count": 2571
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"R",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"R-CRAN-recommended"
]
},
{
"type": "run",
"ports": [
"R"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"R-distrom",
"R-textir",
"R-bolasso"
]
}
]
},
{
"name": "R-ggcharts",
"portdir": "R/R-ggcharts",
"version": "0.2.1",
"license": "MIT",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://thomas-neitmann.github.io/ggcharts/index.html",
"description": "Shorten the distance from data visualization idea to actual plot",
"long_description": "Shorten the distance from data visualization idea to actual plot",
"active": true,
"categories": [
"graphics",
"science",
"R"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"clang-16",
"R"
]
},
{
"type": "lib",
"ports": [
"R-colorspace",
"R-lifecycle",
"R-dplyr",
"R-ggplot2",
"R-patchwork",
"R-CRAN-recommended",
"R-magrittr",
"R-rlang"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-tibble",
"R-tidyr",
"R-knitr",
"R-scales",
"R-testthat",
"R-rmarkdown",
"R-vdiffr",
"R-lintr",
"R-spelling",
"R-gapminder"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"R-bartcs"
]
}
]
},
{
"name": "R-robcor",
"portdir": "R/R-robcor",
"version": "0.1-6.1",
"license": "(GPL-2 or GPL-3)",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://cran.r-project.org/package=robcor",
"description": "Robust Correlations",
"long_description": "Robust Correlations",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"R",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"R-CRAN-recommended"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-robustbase",
"R-sfsmisc"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"R-uclust",
"R-simts"
]
}
]
},
{
"name": "R-robustfa",
"portdir": "R/R-robustfa",
"version": "1.1-0",
"license": "(GPL-2 or GPL-3)",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://cran.r-project.org/package=robustfa",
"description": "Object-oriented solution for robust factor analysis",
"long_description": "Object-oriented solution for robust factor analysis",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"clang-16",
"R"
]
},
{
"type": "lib",
"ports": [
"R-rrcov",
"R-CRAN-recommended"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-knitr",
"R-rmarkdown",
"R-ellipse",
"R-mclust"
]
}
],
"depends_on": []
},
{
"name": "R-simts",
"portdir": "R/R-simts",
"version": "0.2.2",
"license": "AGPL-3",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://simts.smac-group.com",
"description": "Time series analysis tools",
"long_description": "Time series analysis tools",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [
{
"name": "vital.had",
"github": "barracuda156",
"ports_count": 2571
}
],
"variants": [
"clang10",
"clang11",
"clang12",
"clang13",
"clang14",
"clang15",
"clang16",
"clang50",
"clang60",
"clang70",
"clang80",
"clang90",
"clangdevel",
"g95",
"gcc10",
"gcc11",
"gcc12",
"gcc13",
"gccdevel",
"gfortran"
],
"dependencies": [
{
"type": "build",
"ports": [
"gcc13",
"R",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"R-magrittr",
"R-dplyr",
"R-purrr",
"R-tidyr",
"R-scales",
"R-broom",
"R-robcor",
"R-CRAN-recommended",
"libgcc",
"R-Rcpp",
"R-RcppArmadillo"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-knitr",
"R-rmarkdown"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"R-avar"
]
}
]
},
{
"name": "R-stlplus",
"portdir": "R/R-stlplus",
"version": "0.5.1",
"license": "BSD",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://cran.r-project.org/package=stlplus",
"description": "Enhanced seasonal decomposition of time series",
"long_description": "Enhanced seasonal decomposition of time series",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"clang-16",
"R"
]
},
{
"type": "lib",
"ports": [
"R-yaImpute",
"R-CRAN-recommended",
"R-Rcpp"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-testthat"
]
}
],
"depends_on": [
{
"type": "test",
"ports": [
"R-bfast"
]
}
]
},
{
"name": "R-textir",
"portdir": "R/R-textir",
"version": "2.0-5",
"license": "GPL-3",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://cran.r-project.org/package=textir",
"description": "Inverse regression for text analysis",
"long_description": "Multinomial (inverse) regression inference for text documents and associated attributes.",
"active": true,
"categories": [
"textproc",
"science",
"math",
"R"
],
"maintainers": [
{
"name": "vital.had",
"github": "barracuda156",
"ports_count": 2571
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"R",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"R-distrom",
"R-gamlr",
"R-CRAN-recommended"
]
},
{
"type": "run",
"ports": [
"R"
]
}
],
"depends_on": [
{
"type": "test",
"ports": [
"R-distrom"
]
}
]
},
{
"name": "R-tsBSS",
"portdir": "R/R-tsBSS",
"version": "1.0.0",
"license": "(GPL-2 or GPL-3)",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://cran.r-project.org/package=tsBSS",
"description": "Blind source separation and supervised dimension reduction for time series",
"long_description": "Blind source separation and supervised dimension reduction for time series",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [],
"variants": [
"clang10",
"clang11",
"clang12",
"clang13",
"clang14",
"clang15",
"clang16",
"clang50",
"clang60",
"clang70",
"clang80",
"clang90",
"clangdevel",
"g95",
"gcc10",
"gcc11",
"gcc12",
"gcc13",
"gccdevel",
"gfortran"
],
"dependencies": [
{
"type": "build",
"ports": [
"gcc13",
"R",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"R-xts",
"R-zoo",
"R-forecast",
"R-BSSprep",
"R-ICtest",
"R-JADE",
"R-CRAN-recommended",
"libgcc",
"R-Rcpp",
"R-RcppArmadillo"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-stochvol",
"R-tsbox",
"R-MTS",
"R-dr"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"R-tensorBSS"
]
}
]
},
{
"name": "R-uclust",
"portdir": "R/R-uclust",
"version": "1.0.0",
"license": "GPL-3",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://cran.r-project.org/package=uclust",
"description": "Clustering and classification inference with u-statistics",
"long_description": "Clustering and classification inference with u-statistics",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"clang-16",
"R"
]
},
{
"type": "lib",
"ports": [
"R-robcor",
"R-CRAN-recommended",
"R-dendextend"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-testthat"
]
}
],
"depends_on": []
},
{
"name": "R-yaImpute",
"portdir": "R/R-yaImpute",
"version": "1.0-34.1",
"license": "GPL-2+",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/jeffreyevans/yaImpute",
"description": "Nearest-neighbor observation imputation and evaluation tools",
"long_description": "Nearest-neighbor observation imputation and evaluation tools",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"R",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"R-CRAN-recommended"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-gam",
"R-gower",
"R-fastICA",
"R-vegan",
"R-ccaPP",
"R-randomForest"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"R-gamlss.ggplots",
"R-stlplus"
]
}
]
},
{
"name": "timoni",
"portdir": "sysutils/timoni",
"version": "0.25.2",
"license": "Apache-2",
"platforms": "darwin freebsd linux",
"epoch": 0,
"replaced_by": null,
"homepage": "https://timoni.sh",
"description": "Timoni is a package manager for Kubernetes, powered by CUE and inspired by Helm.",
"long_description": "Timoni is a package manager for Kubernetes, powered by CUE and inspired by Helm. The Timoni project strives to improve the UX of authoring Kubernetes configs. Instead of mingling Go templates with YAML like Helm, or layering YAML on top of each-other like Kustomize, Timoni relies on cuelang's type safety, code generation and data validation features to offer a better experience of creating, packaging and delivering apps to Kubernetes.",
"active": true,
"categories": [
"sysutils"
],
"maintainers": [
{
"name": "herby.gillot",
"github": "herbygillot",
"ports_count": 1019
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"go",
"clang-18"
]
}
],
"depends_on": []
},
{
"name": "R-BGGM",
"portdir": "R/R-BGGM",
"version": "2.1.4",
"license": "GPL-2",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://donaldrwilliams.github.io/BGGM",
"description": "Bayesian Gaussian Graphical Models",
"long_description": "Bayesian Gaussian Graphical Models",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [
{
"name": "vital.had",
"github": "barracuda156",
"ports_count": 2571
}
],
"variants": [
"clang11",
"clang10",
"clang12",
"clang13",
"clang14",
"clang15",
"clang16",
"clang50",
"clang60",
"clang70",
"clang80",
"clang90",
"clangdevel",
"g95",
"gcc10",
"gcc11",
"gcc12",
"gcc13",
"gccdevel",
"gfortran"
],
"dependencies": [
{
"type": "build",
"ports": [
"gcc13",
"R",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"R-RcppProgress",
"R-mvnfast",
"R-reshape",
"R-ggplot2",
"R-ggridges",
"R-Rdpack",
"R-GGally",
"R-network",
"R-sna",
"R-BFpack",
"libgcc13",
"R-CRAN-recommended",
"libgcc",
"R-RcppArmadillo",
"R-RcppDist"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-abind",
"R-knitr",
"R-testthat",
"R-rmarkdown",
"R-psych",
"R-mice",
"R-assortnet",
"R-networktools"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"R-easybgm"
]
},
{
"type": "test",
"ports": [
"R-bayeslincom",
"R-BBcor"
]
}
]
},
{
"name": "R-MPsychoR",
"portdir": "R/R-MPsychoR",
"version": "0.10-8",
"license": "GPL-2",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://cran.r-project.org/package=MPsychoR",
"description": "Modern Psychometrics with R",
"long_description": "Modern Psychometrics with R",
"active": true,
"categories": [
"science",
"R"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"R",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"R-CRAN-recommended"
]
},
{
"type": "run",
"ports": [
"R"
]
}
],
"depends_on": [
{
"type": "test",
"ports": [
"R-smacof"
]
}
]
},
{
"name": "R-ResourceSelection",
"portdir": "R/R-ResourceSelection",
"version": "0.3-6",
"license": "GPL-2",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/psolymos/ResourceSelection",
"description": "Resource selection (probability) functions for use-availability data",
"long_description": "Resource selection (probability) functions for use-availability data",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"R",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"R-pbapply",
"R-CRAN-recommended"
]
},
{
"type": "run",
"ports": [
"R"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"R-RcmdrPlugin.ROC"
]
}
]
},
{
"name": "R-SuperLearner",
"portdir": "R/R-SuperLearner",
"version": "2.0-29",
"license": "GPL-3",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/ecpolley/SuperLearner",
"description": "Implements the super-learner prediction method and contains a library of prediction algorithms to be used in the super-learner",
"long_description": "Implements the super-learner prediction method and contains a library of prediction algorithms to be used in the super-learner",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"clang-16",
"R"
]
},
{
"type": "lib",
"ports": [
"R-cvAUC",
"R-nnls",
"R-CRAN-recommended",
"R-gam"
]
},
{
"type": "run",
"ports": [
"R"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"R-tmle",
"R-ctmle",
"R-nlpred",
"R-drtmle",
"R-AIPW",
"R-lmtp"
]
},
{
"type": "test",
"ports": [
"R-targeted",
"R-ltmle",
"R-medflex",
"R-hal9001",
"R-nestedcv"
]
}
]
},
{
"name": "R-TSSS",
"portdir": "R/R-TSSS",
"version": "1.3.4-5",
"license": "GPL-2+",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://cran.r-project.org/package=TSSS",
"description": "Time Series Analysis with State Space Model",
"long_description": "Time Series Analysis with State Space Model",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [],
"variants": [
"clang10",
"clang11",
"clang12",
"clang13",
"clang14",
"clang15",
"clang16",
"clang50",
"clang60",
"clang70",
"clang80",
"clang90",
"clangdevel",
"g95",
"gcc10",
"gcc11",
"gcc12",
"gcc13",
"gccdevel",
"gfortran"
],
"dependencies": [
{
"type": "build",
"ports": [
"R",
"clang-16",
"gcc13"
]
},
{
"type": "lib",
"ports": [
"libgcc",
"R-CRAN-recommended"
]
},
{
"type": "run",
"ports": [
"R"
]
}
],
"depends_on": []
},
{
"name": "R-assortnet",
"portdir": "R/R-assortnet",
"version": "0.20",
"license": "GPL-2",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://cran.r-project.org/package=assortnet",
"description": "Calculate the assortativity coefficient of weighted and binary networks",
"long_description": "Calculate the assortativity coefficient of weighted and binary networks",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"R",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"R-CRAN-recommended"
]
},
{
"type": "run",
"ports": [
"R"
]
}
],
"depends_on": [
{
"type": "test",
"ports": [
"R-BGGM"
]
}
]
},
{
"name": "R-bayeslincom",
"portdir": "R/R-bayeslincom",
"version": "1.3.0",
"license": "GPL-2",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://cran.r-project.org/package=bayeslincom",
"description": "Linear combinations of Bayesian posterior samples",
"long_description": "Linear combinations of Bayesian posterior samples",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"R",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"R-ggplot2",
"R-CRAN-recommended"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-BGGM",
"R-testthat"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"R-BBcor"
]
}
]
},
{
"name": "R-bws",
"portdir": "R/R-bws",
"version": "0.1.0",
"license": "GPL-2+",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://cran.r-project.org/package=bws",
"description": "Bayesian Weighted Sums",
"long_description": "An interface to the Bayesian Weighted Sums model implemented in Stan. It estimates the summed effect of multiple, often moderately to highly correlated, continuous predictors.",
"active": true,
"categories": [
"science",
"R"
],
"maintainers": [
{
"name": "vital.had",
"github": "barracuda156",
"ports_count": 2571
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"clang-16",
"R"
]
},
{
"type": "lib",
"ports": [
"R-RcppEigen",
"R-RcppParallel",
"R-StanHeaders",
"R-rstantools",
"R-rstan",
"R-CRAN-recommended",
"R-BH",
"R-Rcpp"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-testthat"
]
}
],
"depends_on": []
},
{
"name": "R-calibrate",
"portdir": "R/R-calibrate",
"version": "1.7.7",
"license": "GPL-2",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://cran.r-project.org/package=calibrate",
"description": "Calibration of scatterplot and biplot axes",
"long_description": "Calibration of scatterplot and biplot axes",
"active": true,
"categories": [
"science",
"R"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"R",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"R-CRAN-recommended"
]
},
{
"type": "run",
"ports": [
"R"
]
}
],
"depends_on": [
{
"type": "test",
"ports": [
"R-smacof"
]
}
]
},
{
"name": "R-candisc",
"portdir": "R/R-candisc",
"version": "0.9.0",
"license": "GPL-2+",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://friendly.github.io/candisc",
"description": "Visualize generalized canonical discriminant and canonical correlation analysis",
"long_description": "Visualize generalized canonical discriminant and canonical correlation analysis",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"R",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"R-heplots",
"R-CRAN-recommended",
"R-car"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-rpart.plot",
"R-knitr",
"R-rmarkdown",
"R-carData",
"R-rgl",
"R-corrplot"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"R-SurveyCC"
]
},
{
"type": "test",
"ports": [
"R-heplots"
]
}
]
},
{
"name": "R-cocor",
"portdir": "R/R-cocor",
"version": "1.1-4",
"license": "GPL-3+",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://cran.r-project.org/package=cocor",
"description": "Statistical tests for the comparison between two correlations based on either independent or dependent groups",
"long_description": "Statistical tests for the comparison between two correlations based on either independent or dependent groups",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"R",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"R-CRAN-recommended"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-testthat"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"R-networktools"
]
},
{
"type": "test",
"ports": [
"R-umx",
"R-rmcorr"
]
}
]
},
{
"name": "R-ctmle",
"portdir": "R/R-ctmle",
"version": "0.1.2",
"license": "GPL-2",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://cran.r-project.org/package=ctmle",
"description": "Collaborative Targeted Maximum Likelihood Estimation",
"long_description": "Collaborative Targeted Maximum Likelihood Estimation",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"clang-16",
"R"
]
},
{
"type": "lib",
"ports": [
"R-tmle",
"R-CRAN-recommended",
"R-glmnet",
"R-SuperLearner"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-dplyr",
"R-knitr",
"R-testthat",
"R-rmarkdown"
]
}
],
"depends_on": []
},
{
"name": "R-cvAUC",
"portdir": "R/R-cvAUC",
"version": "1.1.4",
"license": "Apache-2",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/ledell/cvAUC",
"description": "Cross-validated area under the ROC curve confidence intervals",
"long_description": "Cross-validated area under the ROC curve confidence intervals",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"R",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"R-data.table",
"R-ROCR",
"R-CRAN-recommended"
]
},
{
"type": "run",
"ports": [
"R"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"R-nlpred",
"R-psfmi",
"R-SuperLearner"
]
}
]
},
{
"name": "R-drtmle",
"portdir": "R/R-drtmle",
"version": "1.1.2",
"license": "MIT",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://cran.r-project.org/package=drtmle",
"description": "Doubly-robust nonparametric estimation and inference",
"long_description": "Doubly-robust nonparametric estimation and inference",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"R",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"R-SuperLearner",
"R-future.apply",
"R-np",
"R-CRAN-recommended"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-foreach",
"R-gam",
"R-stringi",
"R-knitr",
"R-testthat",
"R-nloptr",
"R-rmarkdown",
"R-quadprog"
]
}
],
"depends_on": []
},
{
"name": "R-eigenmodel",
"portdir": "R/R-eigenmodel",
"version": "1.11",
"license": "GPL-2",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://pdhoff.github.io",
"description": "Semi-parametric factor and regression models for symmetric relational data",
"long_description": "Semi-parametric factor and regression models for symmetric relational data",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"R",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"R-CRAN-recommended"
]
},
{
"type": "run",
"ports": [
"R"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"R-networktools"
]
}
]
},
{
"name": "R-fcirt",
"portdir": "R/R-fcirt",
"version": "0.1.0.9000",
"license": "GPL-3+",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/Naidantu/fcirt",
"description": "Forced choice in item response theory",
"long_description": "Bayesian estimation of forced choice models in item response theory using RStan.",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [
{
"name": "vital.had",
"github": "barracuda156",
"ports_count": 2571
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"clang-16",
"R"
]
},
{
"type": "lib",
"ports": [
"R-RcppEigen",
"R-RcppParallel",
"R-StanHeaders",
"R-numDeriv",
"R-rstantools",
"R-rstan",
"R-CRAN-recommended",
"R-BH",
"R-Rcpp"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-knitr",
"R-rmarkdown"
]
}
],
"depends_on": []
},
{
"name": "R-hbamr",
"portdir": "R/R-hbamr",
"version": "2.3.2",
"license": "GPL-3+",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://jbolstad.github.io/hbamr",
"description": "Hierarchical Bayesian Aldrich–McKelvey scaling via Stan",
"long_description": "Perform hierarchical Bayesian Aldrich–McKelvey scaling using Hamiltonian Monte Carlo via Stan. Aldrich–McKelvey (AM) scaling is a method for estimating the ideological positions of survey respondents and political actors on a common scale using positional survey data.",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [
{
"name": "vital.had",
"github": "barracuda156",
"ports_count": 2571
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"clang-16",
"R"
]
},
{
"type": "lib",
"ports": [
"R-RcppEigen",
"R-RcppParallel",
"R-StanHeaders",
"R-rlang",
"R-colorspace",
"R-plyr",
"R-rstantools",
"R-dplyr",
"R-loo",
"R-matrixStats",
"R-progressr",
"R-tidyr",
"R-RColorBrewer",
"R-ggplot2",
"R-rstan",
"R-future",
"R-future.apply",
"R-pbmcapply",
"R-CRAN-recommended",
"R-BH",
"R-Rcpp"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-data.table",
"R-knitr",
"R-rmarkdown"
]
}
],
"depends_on": []
},
{
"name": "R-jomo",
"portdir": "R/R-jomo",
"version": "2.7-6",
"license": "GPL-2",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://cran.r-project.org/package=jomo",
"description": "Multi-level joint modelling multiple imputation",
"long_description": "Multi-level joint modelling multiple imputation",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"clang-16",
"R"
]
},
{
"type": "lib",
"ports": [
"R-tibble",
"R-lme4",
"R-CRAN-recommended",
"R-ordinal"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-mitml"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"R-mitml"
]
}
]
},
{
"name": "R-ltmle",
"portdir": "R/R-ltmle",
"version": "1.3-0",
"license": "GPL-2",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://joshuaschwab.github.io/ltmle",
"description": "Longitudinal Targeted Maximum Likelihood Estimation",
"long_description": "Longitudinal Targeted Maximum Likelihood Estimation",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"R",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"R-CRAN-recommended",
"R-matrixStats"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-arm",
"R-SuperLearner",
"R-tmle",
"R-nnls",
"R-knitr",
"R-testthat",
"R-rmarkdown"
]
}
],
"depends_on": []
},
{
"name": "R-mitml",
"portdir": "R/R-mitml",
"version": "0.4-5",
"license": "(GPL-2 or GPL-3)",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://cran.r-project.org/package=mitml",
"description": "Tools for multiple imputation in multi-level modelling",
"long_description": "Tools for multiple imputation in multi-level modelling",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"clang-16",
"R"
]
},
{
"type": "lib",
"ports": [
"R-haven",
"R-CRAN-recommended",
"R-jomo",
"R-pan"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-geepack",
"R-glmmTMB",
"R-miceadds",
"R-Amelia",
"R-knitr",
"R-lavaan",
"R-lme4",
"R-rmarkdown",
"R-mice"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"R-mice",
"R-psfmi"
]
},
{
"type": "test",
"ports": [
"R-jomo"
]
}
]
},
{
"name": "R-nestedcv",
"portdir": "R/R-nestedcv",
"version": "0.7.12",
"license": "MIT",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/myles-lewis/nestedcv",
"description": "Nested cross-validation with R-glmnet and R-caret",
"long_description": "Nested cross-validation with R-glmnet and R-caret",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [
{
"name": "vital.had",
"github": "barracuda156",
"ports_count": 2571
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"clang-16",
"R"
]
},
{
"type": "lib",
"ports": [
"R-matrixStats",
"R-ggplot2",
"R-doParallel",
"R-foreach",
"R-pROC",
"R-caret",
"R-glmnet",
"R-RhpcBLASctl",
"R-matrixTests",
"R-ROCR",
"R-CRAN-recommended",
"R-Rfast",
"R-rlang",
"R-data.table"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-Boruta",
"R-RcppEigen",
"R-knitr",
"R-rmarkdown",
"R-randomForest",
"R-pbapply",
"R-ranger",
"R-gbm",
"R-mlbench",
"R-hsstan",
"R-ggbeeswarm",
"R-ggpubr",
"R-pls",
"R-SuperLearner",
"R-mda",
"R-fastshap",
"R-CORElearn"
]
}
],
"depends_on": []
},
{
"name": "R-networktools",
"portdir": "R/R-networktools",
"version": "1.5.2",
"license": "GPL-3",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/paytonjjones/networktools",
"description": "Tools for identifying important nodes in networks",
"long_description": "Tools for identifying important nodes in networks",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [
{
"name": "vital.had",
"github": "barracuda156",
"ports_count": 2571
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"clang-16",
"R"
]
},
{
"type": "lib",
"ports": [
"R-ggplot2",
"R-gridExtra",
"R-igraph",
"R-psych",
"R-qgraph",
"R-R.utils",
"R-cocor",
"R-eigenmodel",
"R-smacof",
"R-wordcloud",
"R-CRAN-recommended",
"R-reshape2",
"R-RColorBrewer"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-dplyr",
"R-testthat"
]
}
],
"depends_on": [
{
"type": "test",
"ports": [
"R-BGGM"
]
}
]
},
{
"name": "R-pan",
"portdir": "R/R-pan",
"version": "1.9",
"license": "GPL-3",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://cran.r-project.org/package=pan",
"description": "Multiple imputation for multivariate panel or clustered data",
"long_description": "Multiple imputation for multivariate panel or clustered data",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [],
"variants": [
"clang10",
"clang11",
"clang12",
"clang13",
"clang14",
"clang15",
"clang16",
"clang50",
"clang60",
"clang70",
"clang80",
"clang90",
"clangdevel",
"g95",
"gcc10",
"gcc11",
"gcc12",
"gcc13",
"gccdevel",
"gfortran"
],
"dependencies": [
{
"type": "build",
"ports": [
"gcc13",
"R",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"R-CRAN-recommended",
"libgcc",
"R-mitools",
"R-lme4"
]
},
{
"type": "run",
"ports": [
"R"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"R-mitml"
]
},
{
"type": "test",
"ports": [
"R-mice"
]
}
]
},
{
"name": "R-pdqr",
"portdir": "R/R-pdqr",
"version": "0.3.1",
"license": "MIT",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://echasnovski.github.io/pdqr",
"description": "Create, transform and summarize custom random variables with distribution functions",
"long_description": "Create, transform and summarize custom random variables with distribution functions",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [
{
"name": "vital.had",
"github": "barracuda156",
"ports_count": 2571
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"R",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"R-CRAN-recommended"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-knitr",
"R-testthat",
"R-rmarkdown",
"R-covr",
"R-vdiffr",
"R-spelling",
"R-pillar"
]
}
],
"depends_on": []
},
{
"name": "R-prefmod",
"portdir": "R/R-prefmod",
"version": "0.8-36",
"license": "GPL-2+",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://cran.r-project.org/package=prefmod",
"description": "Utilities to fit paired comparison models for preferences",
"long_description": "Utilities to fit paired comparison models for preferences",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [],
"variants": [
"clang10",
"clang11",
"clang12",
"clang13",
"clang14",
"clang15",
"clang16",
"clang50",
"clang60",
"clang70",
"clang80",
"clang90",
"clangdevel",
"g95",
"gcc10",
"gcc11",
"gcc12",
"gcc13",
"gccdevel",
"gfortran"
],
"dependencies": [
{
"type": "build",
"ports": [
"gcc13",
"R",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"R-CRAN-recommended",
"libgcc",
"R-colorspace",
"R-gnm"
]
},
{
"type": "run",
"ports": [
"R"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"R-PLMIX"
]
},
{
"type": "test",
"ports": [
"R-PlackettLuce",
"R-BradleyTerry2",
"R-smacof"
]
}
]
},
{
"name": "R-psfmi",
"portdir": "R/R-psfmi",
"version": "1.4.0",
"license": "(GPL-2 or GPL-3)",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://mwheymans.github.io/psfmi",
"description": "Prediction model pooling, selection and performance evaluation across multiply imputed datasets",
"long_description": "Prediction model pooling, selection and performance evaluation across multiply imputed datasets",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [
{
"name": "vital.had",
"github": "barracuda156",
"ports_count": 2571
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"clang-16",
"R"
]
},
{
"type": "lib",
"ports": [
"R-stringr",
"R-tibble",
"R-dplyr",
"R-purrr",
"R-tidyr",
"R-ggplot2",
"R-lme4",
"R-pROC",
"R-car",
"R-rsample",
"R-mice",
"R-rms",
"R-norm",
"R-cvAUC",
"R-mitml",
"R-CRAN-recommended",
"R-magrittr",
"R-mitools"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-gtools",
"R-knitr",
"R-testthat",
"R-rmarkdown",
"R-readr",
"R-covr",
"R-bookdown"
]
}
],
"depends_on": []
},
{
"name": "R-robeth",
"portdir": "R/R-robeth",
"version": "2.7-8",
"license": "GPL-2+",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://cran.r-project.org/package=robeth",
"description": "R functions for robust statistics",
"long_description": "R functions for robust statistics",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [],
"variants": [
"clang10",
"clang11",
"clang12",
"clang13",
"clang14",
"clang15",
"clang16",
"clang50",
"clang60",
"clang70",
"clang80",
"clang90",
"clangdevel",
"g95",
"gcc10",
"gcc11",
"gcc12",
"gcc13",
"gccdevel",
"gfortran"
],
"dependencies": [
{
"type": "build",
"ports": [
"R",
"clang-16",
"gcc13"
]
},
{
"type": "lib",
"ports": [
"libgcc",
"R-CRAN-recommended"
]
},
{
"type": "run",
"ports": [
"R"
]
}
],
"depends_on": []
},
{
"name": "R-smacof",
"portdir": "R/R-smacof",
"version": "2.1-7",
"license": "GPL-3",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://cran.r-project.org/package=smacof",
"description": "Multi-dimensional scaling",
"long_description": "Multi-dimensional scaling",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"clang-16",
"R"
]
},
{
"type": "lib",
"ports": [
"R-nnls",
"R-Hmisc",
"R-doParallel",
"R-foreach",
"R-polynom",
"R-plotrix",
"R-ellipse",
"R-weights",
"R-wordcloud",
"R-CRAN-recommended",
"R-e1071",
"R-colorspace"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-ggplot2",
"R-knitr",
"R-rmarkdown",
"R-MPsychoR",
"R-calibrate",
"R-prefmod"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"R-networktools"
]
},
{
"type": "test",
"ports": [
"R-seriation"
]
}
]
},
{
"name": "R-surveil",
"portdir": "R/R-surveil",
"version": "0.3.0",
"license": "GPL-3+",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://connordonegan.github.io/surveil",
"description": "Time series models for disease surveillance",
"long_description": "Fits time series models for routine disease surveillance tasks and returns probability distributions for a variety of quantities of interest, including age-standardized rates, period and cumulative percent change and measures of health inequality.",
"active": true,
"categories": [
"science",
"R"
],
"maintainers": [
{
"name": "vital.had",
"github": "barracuda156",
"ports_count": 2571
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"clang-16",
"R"
]
},
{
"type": "lib",
"ports": [
"R-RcppEigen",
"R-RcppParallel",
"R-StanHeaders",
"R-rlang",
"R-rstantools",
"R-dplyr",
"R-tidyr",
"R-ggplot2",
"R-gridExtra",
"R-rstan",
"R-scales",
"R-ggdist",
"R-tidybayes",
"R-CRAN-recommended",
"R-BH",
"R-Rcpp"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-knitr",
"R-testthat",
"R-rmarkdown"
]
}
],
"depends_on": []
},
{
"name": "R-tmle",
"portdir": "R/R-tmle",
"version": "2.0.1.1",
"license": "(BSD or GPL-2)",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://cran.r-project.org/package=tmle",
"description": "Targeted Maximum Likelihood Estimation",
"long_description": "Targeted Maximum Likelihood Estimation",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"clang-16",
"R"
]
},
{
"type": "lib",
"ports": [
"R-CRAN-recommended",
"R-glmnet",
"R-SuperLearner"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-gam",
"R-dbarts",
"R-ROCR",
"R-WeightedROC"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"R-ctmle"
]
},
{
"type": "test",
"ports": [
"R-AIPW",
"R-ltmle",
"R-tmle3",
"R-bartCause"
]
}
]
},
{
"name": "R-wordcloud",
"portdir": "R/R-wordcloud",
"version": "2.6",
"license": "LGPL-2.1",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://cran.r-project.org/package=wordcloud",
"description": "Word clouds",
"long_description": "Word clouds",
"active": true,
"categories": [
"science",
"R"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"clang-16",
"R"
]
},
{
"type": "lib",
"ports": [
"R-CRAN-recommended",
"R-Rcpp",
"R-RColorBrewer"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-slam",
"R-tm"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"R-RNewsflow",
"R-networktools",
"R-shinyr",
"R-GNAR",
"R-smacof"
]
},
{
"type": "test",
"ports": [
"R-tidyjson",
"R-stm",
"R-textmineR"
]
}
]
},
{
"name": "R-ACDm",
"portdir": "R/R-ACDm",
"version": "1.0.4.3",
"license": "GPL-2+",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://cran.r-project.org/package=ACDm",
"description": "Tools for autoregressive conditional duration models",
"long_description": "Tools for autoregressive conditional duration models",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [],
"variants": [
"clang10",
"clang11",
"clang12",
"clang13",
"clang14",
"clang15",
"clang16",
"clang50",
"clang60",
"clang70",
"clang80",
"clang90",
"clangdevel",
"g95",
"gcc10",
"gcc11",
"gcc12",
"gcc13",
"gccdevel",
"gfortran"
],
"dependencies": [
{
"type": "build",
"ports": [
"gcc13",
"R",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"R-dplyr",
"R-ggplot2",
"R-Rsolnp",
"R-CRAN-recommended",
"libgcc",
"R-plyr",
"R-zoo"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-optimx",
"R-rgl"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"R-eNchange"
]
}
]
},
{
"name": "R-BDgraph",
"portdir": "R/R-BDgraph",
"version": "2.73",
"license": "GPL-2+",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://cran.r-project.org/package=BDgraph",
"description": "Bayesian structure learning in graphical models using birth-death MCMC",
"long_description": "Bayesian structure learning in graphical models using birth-death MCMC",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [
{
"name": "vital.had",
"github": "barracuda156",
"ports_count": 2571
}
],
"variants": [
"clang10",
"clang11",
"clang12",
"clang13",
"clang14",
"clang15",
"clang16",
"clang50",
"clang60",
"clang70",
"clang80",
"clang90",
"clangdevel",
"g95",
"gcc10",
"gcc11",
"gcc12",
"gcc13",
"gccdevel",
"gfortran"
],
"dependencies": [
{
"type": "build",
"ports": [
"gcc13",
"R",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"R-pROC",
"libgcc13",
"R-CRAN-recommended",
"libgcc",
"R-ggplot2",
"R-igraph"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-knitr",
"R-rmarkdown",
"R-tmvtnorm",
"R-huge",
"R-skimr",
"R-ssgraph"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"R-heteromixgm",
"R-bayesWatch",
"R-easybgm",
"R-ssgraph"
]
},
{
"type": "test",
"ports": [
"R-BayesSUR",
"R-qgraph"
]
}
]
},
{
"name": "R-BayesQVGEL",
"portdir": "R/R-BayesQVGEL",
"version": "0.1.2",
"license": "GPL-2",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://cran.r-project.org/package=BayesQVGEL",
"description": "Bayesian quantile variable selection for G–E in longitudinal studies",
"long_description": "Bayesian quantile variable selection for G–E in longitudinal studies",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [],
"variants": [
"clang10",
"clang11",
"clang12",
"clang13",
"clang14",
"clang15",
"clang16",
"clang50",
"clang60",
"clang70",
"clang80",
"clang90",
"clangdevel",
"g95",
"gcc10",
"gcc11",
"gcc12",
"gcc13",
"gccdevel",
"gfortran"
],
"dependencies": [
{
"type": "build",
"ports": [
"gcc13",
"R",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"R-CRAN-recommended",
"libgcc",
"R-Rcpp",
"R-RcppArmadillo"
]
},
{
"type": "run",
"ports": [
"R"
]
}
],
"depends_on": []
},
{
"name": "R-Bergm",
"portdir": "R/R-Bergm",
"version": "5.0.7",
"license": "GPL-2+",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://acaimo.github.io/Bergm",
"description": "Bayesian Exponential Random Graph Models",
"long_description": "Bayesian analysis for exponential random graph models using advanced computational algorithms.",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [
{
"name": "vital.had",
"github": "barracuda156",
"ports_count": 2571
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"clang-16",
"R"
]
},
{
"type": "lib",
"ports": [
"R-matrixcalc",
"R-statnet.common",
"R-MCMCpack",
"R-network",
"R-Rglpk",
"R-ergm",
"R-CRAN-recommended",
"R-coda",
"R-mvtnorm"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-spelling"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"R-BFpack"
]
},
{
"type": "test",
"ports": [
"R-btergm",
"R-texreg"
]
}
]
},
{
"name": "R-MIRES",
"portdir": "R/R-MIRES",
"version": "0.1.0",
"license": "MIT",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/stephenSRMMartin/MIRES",
"description": "Measurement invariance assessment using random effects models and shrinkage",
"long_description": "Measurement invariance assessment using random effects models and shrinkage",
"active": true,
"categories": [
"science",
"math",
"R"
],
"maintainers": [
{
"name": "vital.had",
"github": "barracuda156",
"ports_count": 2571
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"clang-16",
"R"
]
},
{
"type": "lib",
"ports": [
"R-RcppEigen",
"R-StanHeaders",
"R-cubature",
"R-mvtnorm",
"R-rstantools",
"R-truncnorm",
"R-rstan",
"R-HDInterval",
"R-Formula",
"R-pracma",
"R-logspline",
"R-dirichletprocess",
"R-CRAN-recommended",
"R-BH",
"R-Rcpp"
]
},
{
"type": "run",
"ports": [
"R"
]
},
{
"type": "test",
"ports": [
"R-testthat"
]
}
],
"depends_on": []
}
]
}