{"count":51956,"next":"https://ports.macports.org/api/v1/ports/?format=json&ordering=-name&page=131","previous":"https://ports.macports.org/api/v1/ports/?format=json&ordering=-name&page=129","results":[{"name":"R-fastglm","portdir":"R/R-fastglm","version":"0.0.3","license":"GPL-2+","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://github.com/jaredhuling/fastglm","description":"Fast and stable fitting of generalized linear models using RcppEigen","long_description":"Fast and stable fitting of generalized linear models using RcppEigen","active":true,"categories":["science","math","R"],"maintainers":[],"variants":["clang13","clang14","clang15","clang16","clang17","clang18","clang19","clangdevel","g95","gcc10","gcc11","gcc12","gcc13","gcc14","gccdevel","gfortran"],"dependencies":[{"type":"build","ports":["clang-19","R","gcc14"]},{"type":"lib","ports":["R-RcppEigen","R-bigmemory","R-CRAN-recommended","libgcc14","libgcc","R-BH","R-Rcpp"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-knitr","R-rmarkdown","R-glm2"]}],"depends_on":[{"type":"lib","ports":["R-DRDID","R-FBMS","R-crctStepdown","R-fastcpd"]},{"type":"test","ports":["R-btergm"]}]},{"name":"R-fastGHQuad","portdir":"R/R-fastGHQuad","version":"1.0.1","license":"MIT","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=fastGHQuad","description":"Fast Rcpp implementation of Gauss–Hermite quadrature","long_description":"Fast Rcpp implementation of Gauss–Hermite quadrature","active":true,"categories":["science","math","R"],"maintainers":[],"variants":["clang13","clang14","clang15","clang16","clang17","clang18","clang19","clangdevel","g95","gcc10","gcc11","gcc12","gcc13","gcc14","gccdevel","gfortran"],"dependencies":[{"type":"build","ports":["clang-19","R","gcc14"]},{"type":"lib","ports":["libgcc14","libgcc","R-Rcpp","R-CRAN-recommended"]},{"type":"run","ports":["R"]}],"depends_on":[{"type":"lib","ports":["R-sfaR","R-metaplus","R-mixAK","R-lavacreg","R-randomLCA","R-robmixglm","R-robustlmm","R-rstpm2"]},{"type":"test","ports":["R-mlr3mbo"]}]},{"name":"R-FastGaSP","portdir":"R/R-FastGaSP","version":"0.5.3","license":"GPL-2+","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=FastGaSP","description":"Fast and exact computation of Gaussian stochastic process","long_description":"Fast and exact computation of Gaussian stochastic process","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-Rcpp","R-RcppEigen","R-CRAN-recommended"]},{"type":"run","ports":["R"]}],"depends_on":[]},{"name":"R-fasterize","portdir":"R/R-fasterize","version":"1.0.5","license":"MIT","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://github.com/ecohealthalliance/fasterize","description":"Fast polygon to raster conversion","long_description":"Fast polygon to raster conversion","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-raster","R-wk","R-CRAN-recommended","R-Rcpp","R-RcppArmadillo"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-knitr","R-testthat","R-rmarkdown","R-microbenchmark","R-spelling","R-geos","R-sf"]}],"depends_on":[]},{"name":"R-fastDummies","portdir":"R/R-fastDummies","version":"1.7.4","license":"MIT","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://jacobkap.github.io/fastDummies","description":"Fast creation of dummy (binary) columns and rows from categorical variables","long_description":"Fast creation of dummy (binary) columns and rows from categorical variables","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-tibble","R-CRAN-recommended","R-data.table","R-stringr"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-knitr","R-testthat","R-rmarkdown","R-covr","R-spelling"]}],"depends_on":[{"type":"lib","ports":["R-spooky","R-MplusAutomation","R-Seurat","R-TSCI","R-cbcTools","R-drf","R-jenga","R-GenMarkov","R-naive","R-nlive","R-segen"]},{"type":"test","ports":["R-logitr"]}]},{"name":"R-fastcpd","portdir":"R/R-fastcpd","version":"0.14.6","license":"GPL-3+","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://fastcpd.xingchi.li","description":"Fast change point detection via sequential gradient descent","long_description":"Fast change point detection via sequential gradient descent","active":true,"categories":["science","math","R"],"maintainers":[],"variants":["clang13","clang14","clang15","clang16","clang17","clang18","clang19","clangdevel","g95","gcc10","gcc11","gcc12","gcc13","gcc14","gccdevel","gfortran"],"dependencies":[{"type":"build","ports":["clang-19","R","gcc14"]},{"type":"lib","ports":["R-testthat","R-forecast","R-tseries","R-glmnet","R-RcppClock","R-fastglm","R-CRAN-recommended","libgcc14","libgcc","R-RcppArmadillo","R-progress","R-Rcpp"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-mosum","R-abind","R-xml2","R-mvtnorm","R-numDeriv","R-zoo","R-dplyr","R-matrixStats","R-reshape2","R-ggplot2","R-gridExtra","R-knitr","R-lubridate","R-testthat","R-rmarkdown","R-mockthat"]}],"depends_on":[]},{"name":"R-fastcmh","portdir":"R/R-fastcmh","version":"0.2.7","license":"(GPL-2 or GPL-3)","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=fastcmh","description":"Significant interval discovery with categorical covariates","long_description":"Significant interval discovery with categorical covariates","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-CRAN-recommended","R-bindata","R-Rcpp"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-testthat"]}],"depends_on":[]},{"name":"R-fastcluster","portdir":"R/R-fastcluster","version":"1.2.6","license":"(BSD or GPL-2)","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://danifold.net/fastcluster.html","description":"Fast hierarchical clustering routines for R","long_description":"Fast hierarchical clustering routines for R","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-CRAN-recommended"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-flashClust"]}],"depends_on":[{"type":"lib","ports":["R-NPflow","R-WeightedCluster","R-maotai"]}]},{"name":"R-fastAFT","portdir":"R/R-fastAFT","version":"1.4","license":"GPL-2+","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=fastAFT","description":"Fast regression for the accelerated failure time (AFT) model","long_description":"Fast regression for the accelerated failure time (AFT) model","active":true,"categories":["science","math","R"],"maintainers":[],"variants":["clang13","clang14","clang15","clang16","clang17","clang18","clang19","clangdevel","g95","gcc10","gcc11","gcc12","gcc13","gcc14","gccdevel","gfortran"],"dependencies":[{"type":"build","ports":["clang-19","R","gcc14"]},{"type":"lib","ports":["libgcc","R-CRAN-recommended","libgcc14"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-knitr","R-rmarkdown"]}],"depends_on":[]},{"name":"R-fastadi","portdir":"R/R-fastadi","version":"0.1.1","license":"MIT","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://github.com/RoheLab/fastadi","description":"Self-tuning data-adaptive matrix imputation","long_description":"Self-tuning data-adaptive matrix imputation","active":true,"categories":["science","math","R"],"maintainers":[],"variants":["clang13","clang14","clang15","clang16","clang17","clang18","clang19","clangdevel","g95","gcc10","gcc11","gcc12","gcc13","gcc14","gccdevel","gfortran"],"dependencies":[{"type":"build","ports":["clang-19","R","gcc14"]},{"type":"lib","ports":["R-glue","R-ellipsis","R-RSpectra","R-LRMF3","R-logger","R-CRAN-recommended","libgcc14","libgcc","R-Rcpp","R-RcppArmadillo"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-knitr","R-testthat","R-rmarkdown","R-covr","R-invertiforms"]}],"depends_on":[]},{"name":"R-fasta","portdir":"R/R-fasta","version":"0.1.0","license":"MIT","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=fasta","description":"Fast Adaptive Shrinkage/Thresholding Algorithm","long_description":"Fast Adaptive Shrinkage/Thresholding Algorithm","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-CRAN-recommended"]},{"type":"run","ports":["R"]}],"depends_on":[]},{"name":"R-farver","portdir":"R/R-farver","version":"2.1.2","license":"MIT","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://farver.data-imaginist.com","description":"High-performance color space manipulation","long_description":"High-performance color space manipulation","active":true,"categories":["graphics","science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-CRAN-recommended"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-testthat","R-covr"]}],"depends_on":[{"type":"lib","ports":["R-ggblanket","R-patchwork","R-prismatic","R-scales","R-thematic","R-tweenr"]}]},{"name":"R-faraway","portdir":"R/R-faraway","version":"1.0.8","license":"(GPL-2 or GPL-3)","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=faraway","description":"Functions and datasets for books by Julian Faraway","long_description":"Functions and datasets for books by Julian Faraway","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-lme4","R-CRAN-recommended"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-leaps"]}],"depends_on":[{"type":"lib","ports":["R-mcen"]},{"type":"test","ports":["R-BayesVarSel","R-aglm","R-BAS","R-fastR2","R-nonnest2","R-assessor"]}]},{"name":"R-far","portdir":"R/R-far","version":"0.6-7","license":"LGPL-2.1","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://github.com/Looping027/far","description":"Modelization for functional auto-regressive processes","long_description":"Modelization for functional auto-regressive processes","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-CRAN-recommended"]},{"type":"run","ports":["R"]}],"depends_on":[]},{"name":"R-fansi","portdir":"R/R-fansi","version":"1.0.6","license":"(GPL-2 or GPL-3)","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=fansi","description":"ANSI control sequence-aware string functions","long_description":"ANSI control sequence-aware string functions","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-CRAN-recommended"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-knitr","R-rmarkdown","R-unitizer"]}],"depends_on":[{"type":"lib","ports":["R-xpectr","R-downlit","R-huxtable","R-pillar","R-tibble"]},{"type":"test","ports":["R-dm","R-pkgdepends","R-colorDF","R-tinytable"]}]},{"name":"R-fanovaGraph","portdir":"R/R-fanovaGraph","version":"1.5","license":"GPL-3","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=fanovaGraph","description":"Kriging models from FANOVA graphs","long_description":"Kriging models from FANOVA graphs","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-sensitivity","R-igraph","R-CRAN-recommended","R-DiceKriging"]},{"type":"run","ports":["R"]}],"depends_on":[]},{"name":"R-fANCOVA","portdir":"R/R-fANCOVA","version":"0.6-1","license":"GPL-3","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=fANCOVA","description":"Non-parametric analysis of covariance","long_description":"Non-parametric analysis of covariance","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-CRAN-recommended"]},{"type":"run","ports":["R"]}],"depends_on":[{"type":"lib","ports":["R-audrex","R-dymo","R-jenga","R-naive","R-segen","R-spooky"]}]},{"name":"R-FAmle","portdir":"R/R-FAmle","version":"1.3.7","license":"GPL-2","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=FAmle","description":"Maximum likelihood and Bayesian estimation of univariate probability distributions","long_description":"Maximum likelihood and Bayesian estimation of univariate probability distributions","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-mvtnorm","R-CRAN-recommended"]},{"type":"run","ports":["R"]}],"depends_on":[]},{"name":"R-fake","portdir":"R/R-fake","version":"1.4.0","license":"GPL-3+","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=fake","description":"Flexible data simulation using the multivariate normal distribution","long_description":"Flexible data simulation using the multivariate normal distribution","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-Rdpack","R-huge","R-CRAN-recommended","R-withr","R-igraph"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-testthat"]}],"depends_on":[{"type":"lib","ports":["R-sharp"]}]},{"name":"R-fairml","portdir":"R/R-fairml","version":"0.8","license":"MIT","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=fairml","description":"Fair models in machine learning","long_description":"Fair models in machine learning","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-glmnet","R-CRAN-recommended"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-gridExtra","R-CVXR","R-cccp"]}],"depends_on":[]},{"name":"R-FAdist","portdir":"R/R-FAdist","version":"2.4","license":"GPL-2","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=FAdist","description":"Probability distributions that are sometimes useful in hydrology","long_description":"Probability distributions that are sometimes useful in hydrology","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-CRAN-recommended"]},{"type":"run","ports":["R"]}],"depends_on":[{"type":"lib","ports":["R-WeibullFit"]},{"type":"test","ports":["R-fitteR"]}]},{"name":"R-Factoshiny","portdir":"R/R-Factoshiny","version":"2.6","license":"GPL-2+","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"http://factominer.free.fr/graphs/factoshiny.html","description":"Perform factorial analysis from R-FactoMineR with an R-shiny application","long_description":"Perform factorial analysis from R-FactoMineR with an R-shiny application","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-DT","R-colourpicker","R-ggrepel","R-shinydashboard","R-FactoMineR","R-ggplot2","R-FactoInvestigate","R-missMDA","R-shinyjqui","R-CRAN-recommended","R-shiny"]},{"type":"run","ports":["R"]}],"depends_on":[{"type":"test","ports":["R-FactoMineR"]}]},{"name":"R-factorstochvol","portdir":"R/R-factorstochvol","version":"1.1.0","license":"GPL-2+","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=factorstochvol","description":"Bayesian estimation of (sparse) latent factor stochastic volatility models","long_description":"Bayesian estimation of (sparse) latent factor stochastic volatility models","active":true,"categories":["science","math","R"],"maintainers":[],"variants":["clang13","clang14","clang15","clang16","clang17","clang18","clang19","clangdevel","g95","gcc10","gcc11","gcc12","gcc13","gcc14","gccdevel","gfortran"],"dependencies":[{"type":"build","ports":["clang-19","R","gcc14"]},{"type":"lib","ports":["R-GIGrvg","R-stochvol","R-corrplot","R-CRAN-recommended","libgcc14","libgcc","R-Rcpp","R-RcppArmadillo"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-coda","R-zoo","R-RColorBrewer","R-knitr","R-testthat","R-LSD"]}],"depends_on":[{"type":"lib","ports":["R-bayesianVARs"]}]},{"name":"R-factor256","portdir":"R/R-factor256","version":"0.1.0","license":"GPL-2","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=factor256","description":"Use raw vectors to minimize memory consumption of factors","long_description":"Use raw vectors to minimize memory consumption of factors","active":true,"categories":["devel","science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-CRAN-recommended"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-data.table","R-tinytest"]}],"depends_on":[]},{"name":"R-FactoMineR","portdir":"R/R-FactoMineR","version":"2.11","license":"GPL-2+","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"http://factominer.free.fr","description":"Multivariate exploratory data analysis and data mining","long_description":"Multivariate exploratory data analysis and data mining","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-ggrepel","R-emmeans","R-car","R-leaps","R-scatterplot3d","R-ellipse","R-flashClust","R-multcompView","R-CRAN-recommended","R-ggplot2","R-DT"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-knitr","R-markdown","R-Factoshiny","R-missMDA"]}],"depends_on":[{"type":"lib","ports":["R-FactoInvestigate","R-Factoshiny","R-GDAtools","R-RcmdrPlugin.FactoMineR","R-factoextra","R-fdm2id","R-mimi","R-missMDA"]}]},{"name":"R-FactoInvestigate","portdir":"R/R-FactoInvestigate","version":"1.9","license":"GPL-2+","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"http://factominer.free.fr/reporting","description":"Automatic description of factorial analysis","long_description":"Automatic description of factorial analysis","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-FactoMineR","R-ggplot2","R-CRAN-recommended","R-rmarkdown"]},{"type":"run","ports":["R"]}],"depends_on":[{"type":"lib","ports":["R-Factoshiny"]}]},{"name":"R-factoextra","portdir":"R/R-factoextra","version":"1.0.7","license":"GPL-2","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://rpkgs.datanovia.com/factoextra/index.html","description":"Extract and visualize the results of multivariate data analyses","long_description":"Extract and visualize the results of multivariate data analyses","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-tidyr","R-ggplot2","R-ggrepel","R-dendextend","R-ggpubr","R-FactoMineR","R-CRAN-recommended","R-abind","R-reshape2"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-knitr","R-igraph","R-mclust","R-ca","R-ade4"]}],"depends_on":[{"type":"test","ports":["R-GDAtools","R-SSLR","R-see"]}]},{"name":"R-facmodCS","portdir":"R/R-facmodCS","version":"1.0","license":"GPL-2","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=facmodCS","description":"Cross-section factor models","long_description":"Cross-section factor models","active":true,"categories":["science","finance","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-zoo","R-tseries","R-robustbase","R-sn","R-data.table","R-RobStatTM","R-CRAN-recommended","R-PerformanceAnalytics","R-xts"]},{"type":"run","ports":["R"]}],"depends_on":[]},{"name":"R-fabricatr","portdir":"R/R-fabricatr","version":"1.0.2","license":"MIT","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://declaredesign.org/r/fabricatr","description":"Imagine your data before you collect it","long_description":"Imagine your data before you collect it","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-CRAN-recommended","R-rlang"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-extraDistr","R-data.table","R-mvnfast","R-estimability","R-testthat"]}],"depends_on":[{"type":"lib","ports":["R-DeclareDesign"]},{"type":"test","ports":["R-CausalQueries","R-estimatr"]}]},{"name":"R-fabMix","portdir":"R/R-fabMix","version":"5.1","license":"GPL-2","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://github.com/mqbssppe/overfittingFABMix","description":"Overfitting Bayesian mixtures of factor analyzers with parsimonious covariance","long_description":"Overfitting Bayesian mixtures of factor analyzers with parsimonious covariance and unknown number of components.","active":true,"categories":["science","math","R"],"maintainers":[],"variants":["clang13","clang14","clang15","clang16","clang17","clang18","clang19","clangdevel","g95","gcc10","gcc11","gcc12","gcc13","gcc14","gccdevel","gfortran"],"dependencies":[{"type":"build","ports":["clang-19","R","gcc14"]},{"type":"lib","ports":["R-coda","R-mvtnorm","R-RColorBrewer","R-ggplot2","R-doParallel","R-foreach","libgcc","R-label.switching","R-mclust","R-CRAN-recommended","libgcc14","R-corrplot","R-Rcpp","R-RcppArmadillo"]},{"type":"run","ports":["R"]}],"depends_on":[{"type":"lib","ports":["R-bpgmm"]}]},{"name":"R-fabletools","portdir":"R/R-fabletools","version":"0.5.0","license":"GPL-3","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://fabletools.tidyverts.org","description":"Core tools for packages in the fable framework","long_description":"Core tools for packages in the fable framework","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-lifecycle","R-vctrs","R-tibble","R-dplyr","R-generics","R-progressr","R-tidyr","R-tidyselect","R-ggplot2","R-scales","R-tsibble","R-distributional","R-ggdist","R-CRAN-recommended","R-R6","R-rlang"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-crayon","R-mvtnorm","R-pillar","R-knitr","R-lubridate","R-testthat","R-future","R-future.apply","R-rmarkdown","R-covr","R-spelling","R-tsibbledata","R-fable","R-feasts"]}],"depends_on":[{"type":"lib","ports":["R-fable","R-fable.prophet","R-feasts"]}]},{"name":"R-fable.prophet","portdir":"R/R-fable.prophet","version":"0.1.0","license":"GPL-3","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://pkg.mitchelloharawild.com/fable.prophet","description":"Prophet modelling interface for fable","long_description":"Prophet modelling interface for fable","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-dplyr","R-lubridate","R-tsibble","R-distributional","R-prophet","R-fabletools","R-CRAN-recommended","R-Rcpp","R-rlang"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-ggplot2","R-knitr","R-testthat","R-rmarkdown","R-covr","R-tsibbledata"]}],"depends_on":[]},{"name":"R-fable","portdir":"R/R-fable","version":"0.4.1","license":"GPL-3","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://fable.tidyverts.org","description":"Forecasting models for tidy time series","long_description":"Forecasting models for tidy time series","active":true,"categories":["science","finance","R","economics"],"maintainers":[],"variants":["clang13","clang14","clang15","clang16","clang17","clang18","clang19","clangdevel","g95","gcc10","gcc11","gcc12","gcc13","gcc14","gccdevel","gfortran"],"dependencies":[{"type":"build","ports":["clang-19","R","gcc14"]},{"type":"lib","ports":["R-tibble","R-dplyr","R-tidyr","R-tsibble","R-distributional","R-fabletools","R-CRAN-recommended","libgcc14","libgcc","R-Rcpp","R-rlang"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-knitr","R-testthat","R-rmarkdown","R-covr","R-forecast","R-spelling","R-tsibbledata","R-feasts","R-MTS"]}],"depends_on":[{"type":"test","ports":["R-fabletools","R-feasts"]}]},{"name":"R-ezplot","portdir":"R/R-ezplot","version":"0.7.13","license":"MIT","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=ezplot","description":"Functions for common chart types","long_description":"Functions for common chart types","active":true,"categories":["graphics","science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-rlang","R-CRAN-recommended","R-dplyr","R-ggplot2","R-lubridate","R-forcats"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-miniUI","R-rmarkdown","R-covr","R-tsibbledata","R-ROCR","R-e1071","R-tibble","R-tidyr","R-knitr","R-shiny","R-testthat","R-tsibble","R-DT"]}],"depends_on":[]},{"name":"R-ezglm","portdir":"R/R-ezglm","version":"1.0","license":"GPL-2","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://code.google.com/archive/p/ezglm","description":"Selects significant non-additive interaction between two variables using fast GLM implementation","long_description":"This package implements a simplified version of least squares and logistic regression for efficiently selecting the significant non-additive interactions between two variables.","active":true,"categories":["science","math","R"],"maintainers":[],"variants":["clang13","clang14","clang15","clang16","clang17","clang18","clang19","clangdevel","g95","gcc10","gcc11","gcc12","gcc13","gcc14","gccdevel","gfortran"],"dependencies":[{"type":"build","ports":["clang-19","R","gcc14"]},{"type":"lib","ports":["R-CRAN-recommended","libgcc14","libgcc"]},{"type":"run","ports":["R"]}],"depends_on":[]},{"name":"R-eyetrackingR","portdir":"R/R-eyetrackingR","version":"0.2.1","license":"MIT","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://samforbes.me/eyetrackingR","description":"Eye-tracking data analysis","long_description":"Eye-tracking data analysis","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-zoo","R-dplyr","R-purrr","R-tidyr","R-ggplot2","R-broom","R-broom.mixed","R-CRAN-recommended","R-lazyeval","R-rlang"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-knitr","R-testthat","R-lme4","R-rmarkdown","R-pbapply","R-doMC","R-foreach","R-glmmTMB"]}],"depends_on":[]},{"name":"R-eyelinkReader","portdir":"R/R-eyelinkReader","version":"1.0.1","license":"GPL-3+","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://alexander-pastukhov.github.io/eyelinkReader","description":"Import gaze data for EyeLink eye tracker","long_description":"Import gaze data for EyeLink eye tracker","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-fs","R-rlang","R-stringr","R-dplyr","R-tidyr","R-ggplot2","R-CRAN-recommended","R-Rcpp","R-RcppProgress"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-knitr","R-testthat","R-rmarkdown"]}],"depends_on":[]},{"name":"R-eyelinker","portdir":"R/R-eyelinker","version":"0.2.1","license":"GPL-3","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=eyelinker","description":"Import ASC files from EyeLink eye-trackers","long_description":"Import ASC files from EyeLink eye-trackers","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-tibble","R-readr","R-intervals","R-CRAN-recommended","R-stringi","R-stringr"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-dplyr","R-tidyr","R-ggplot2","R-knitr","R-testthat","R-rmarkdown","R-covr"]}],"depends_on":[]},{"name":"rexx","portdir":"lang/rexx","version":"3.9.6","license":"LGPL","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"http://regina-rexx.sourceforge.net/","description":"Regina Rexx is an interpreter for the Rexx language","long_description":"Regina is an implementation of the 1996 ANSI Standard for the Rexx language. Rexx is designed to be an easily readable, but powerful scripting and embedded macro language.","active":true,"categories":["lang"],"maintainers":[{"name":"yoav.nir","github":"","ports_count":1}],"variants":["universal"],"dependencies":[{"type":"build","ports":["clang-18"]}],"depends_on":[{"type":"lib","ports":["THE"]}]},{"name":"R-extRemes","portdir":"R/R-extRemes","version":"2.1-4","license":"GPL-2+","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=extRemes","description":"Extreme value analysis","long_description":"Extreme value analysis","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-distillery","R-CRAN-recommended","R-Lmoments"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-fields"]}],"depends_on":[]},{"name":"R-extremefit","portdir":"R/R-extremefit","version":"1.0.2","license":"GPL-2","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=extremefit","description":"Estimation of extreme conditional quantiles and probabilities","long_description":"Estimation of extreme conditional quantiles and probabilities","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-CRAN-recommended"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-R.rsp"]}],"depends_on":[{"type":"test","ports":["R-fitteR"]}]},{"name":"R-ExtremeBounds","portdir":"R/R-ExtremeBounds","version":"0.1.7","license":"GPL-2+","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=ExtremeBounds","description":"Extreme Bounds Analysis (EBA)","long_description":"Extreme Bounds Analysis (EBA)","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-Formula","R-CRAN-recommended"]},{"type":"run","ports":["R"]}],"depends_on":[]},{"name":"R-extras","portdir":"R/R-extras","version":"0.7.3","license":"MIT","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://poissonconsulting.github.io/extras","description":"Helper functions for Bayesian analyses","long_description":"Helper functions for Bayesian analyses","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-chk","R-CRAN-recommended","R-lifecycle"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-ggplot2","R-knitr","R-scales","R-testthat","R-rmarkdown","R-covr","R-viridis","R-sn","R-rlang","R-tibble","R-withr","R-hms","R-tidyr"]}],"depends_on":[{"type":"lib","ports":["R-mcmcr","R-nlist","R-term"]}]},{"name":"R-extraoperators","portdir":"R/R-extraoperators","version":"0.3.0","license":"GPL-3","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://joshuawiley.com/extraoperators","description":"Extra binary relational and logical operators","long_description":"Extra binary relational and logical operators","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-CRAN-recommended"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-testthat","R-rmarkdown","R-covr","R-knitr"]}],"depends_on":[{"type":"lib","ports":["R-brmsmargins","R-multilevelcoda"]}]},{"name":"R-extrafontdb","portdir":"R/R-extrafontdb","version":"1.0","license":"GPL-2","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=extrafontdb","description":"Package for holding the database for the extrafont package","long_description":"Package for holding the database for the extrafont package","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-CRAN-recommended"]},{"type":"run","ports":["R"]}],"depends_on":[{"type":"lib","ports":["R-extrafont"]}]},{"name":"R-extrafont","portdir":"R/R-extrafont","version":"0.19","license":"GPL-2","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://github.com/wch/extrafont","description":"Tools for using fonts","long_description":"Tools for using fonts","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-Rttf2pt1","R-extrafontdb","R-CRAN-recommended"]},{"type":"run","ports":["R"]}],"depends_on":[{"type":"lib","ports":["R-fergm","R-ggalt","R-hrbrthemes"]},{"type":"test","ports":["R-rgl","R-skimr","R-RcmdrPlugin.KMggplot2","R-tagcloud","R-ggmcmc","R-ggthemes"]}]},{"name":"R-extraDistr","portdir":"R/R-extraDistr","version":"1.10.0","license":"GPL-2","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://github.com/twolodzko/extraDistr","description":"Additional univariate and multivariate distributions","long_description":"Additional univariate and multivariate distributions","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-CRAN-recommended","R-Rcpp"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-actuar","R-LaplacesDemon","R-triangle","R-evd","R-testthat","R-VGAM","R-skellam"]}],"depends_on":[{"type":"lib","ports":["R-voteSim","R-BFpack","R-BayesTools","R-prophet","R-simIReff","R-spTimer","R-survstan","R-telescope","R-univariateML","R-BANAM","R-bayespm","R-bellreg","R-convdistr","R-dprop","R-ghypernet","R-iZID","R-jfa","R-kDGLM","R-miscFuncs"]},{"type":"test","ports":["R-SimDesign","R-mvgam","R-fabricatr","R-brms","R-bsitar","R-cbbinom","R-kdensity"]}]},{"name":"R-extendedFamily","portdir":"R/R-extendedFamily","version":"0.2.4","license":"GPL-3","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=extendedFamily","description":"Additional families for generalized linear models","long_description":"Creates family objects identical to stats family but for new links.","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-assertthat","R-CRAN-recommended"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-numDeriv","R-testthat","R-covr"]}],"depends_on":[]},{"name":"R-ExtDist","portdir":"R/R-ExtDist","version":"0.7-2","license":"GPL-2+","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=ExtDist","description":"Extending the range of functions for probability distributions","long_description":"Extending the range of functions for probability distributions","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-optimx","R-CRAN-recommended","R-numDeriv"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-truncdist","R-PerformanceAnalytics","R-SuppDists","R-xtable","R-ggplot2","R-knitr","R-rmarkdown","R-VGAM"]}],"depends_on":[{"type":"lib","ports":["R-noisemodel"]},{"type":"test","ports":["R-fitteR"]}]},{"name":"R-expss","portdir":"R/R-expss","version":"0.11.6","license":"GPL-2+","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://gdemin.github.io/expss","description":"Tables, labels and some useful functions from spreadsheets and SPSS Statistics","long_description":"Tables, labels and some useful functions from spreadsheets and SPSS Statistics","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-data.table","R-CRAN-recommended","R-maditr","R-matrixStats","R-htmlTable"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-huxtable","R-fst","R-repr","R-htmltools","R-ggplot2","R-knitr","R-testthat","R-DT","R-rmarkdown","R-openxlsx"]}],"depends_on":[{"type":"test","ports":["R-crosstable"]}]}]}