{"count":51976,"next":"https://ports.macports.org/api/v1/ports/?format=json&ordering=updated_at&page=283","previous":"https://ports.macports.org/api/v1/ports/?format=json&ordering=updated_at&page=281","results":[{"name":"R-mirtsvd","portdir":"R/R-mirtsvd","version":"1.0","license":"GPL-3","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=mirtsvd","description":"SVD-based estimation for exploratory item factor analysis","long_description":"SVD-based estimation for exploratory item factor analysis","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-GPArotation","R-mirtjml","R-CRAN-recommended"]},{"type":"run","ports":["R"]}],"depends_on":[]},{"name":"R-misc3d","portdir":"R/R-misc3d","version":"0.9-1","license":"(GPL-2 or GPL-3)","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://gitlab.com/luke-tierney/misc3d","description":"Collection of miscellaneous 3D plots, including isosurfaces","long_description":"Collection of miscellaneous 3D plots, including isosurfaces","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-rgl","R-tkrplot"]}],"depends_on":[{"type":"lib","ports":["R-longitudinalData","R-plot3D"]},{"type":"test","ports":["R-ks","R-rgl","R-sm","R-uniformly"]}]},{"name":"R-miscFuncs","portdir":"R/R-miscFuncs","version":"1.5-8","license":"GPL-3","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=miscFuncs","description":"Miscellaneous useful functions including LaTeX tables, Kalman filtering and development tools","long_description":"Miscellaneous useful functions including LaTeX tables, Kalman filtering and development tools","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-roxygen2","R-extraDistr","R-CRAN-recommended","R-mvtnorm"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-bayesGARCH"]}],"depends_on":[]},{"name":"R-miscTools","portdir":"R/R-miscTools","version":"0.6-28","license":"(GPL-2 or GPL-3)","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=miscTools","description":"Miscellaneous tools and utilities","long_description":"Miscellaneous tools and utilities","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-digest","R-CRAN-recommended"]},{"type":"run","ports":["R"]}],"depends_on":[{"type":"lib","ports":["R-Rchoice","R-censReg","R-fastR2","R-maxLik","R-micEcon","R-micEconCES","R-mvProbit","R-robustbetareg","R-sampleSelection"]}]},{"name":"R-miselect","portdir":"R/R-miselect","version":"0.9.2","license":"GPL-3","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=miselect","description":"Variable selection for multiply imputed data","long_description":"Variable selection for multiply imputed data","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-mice","R-knitr","R-testthat","R-rmarkdown"]}],"depends_on":[]},{"name":"R-mispr","portdir":"R/R-mispr","version":"1.0.0","license":"GPL-2","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=mispr","description":"Multiple Imputation with Sequential Penalized Regression","long_description":"Generates multivariate imputations using sequential regression with L2 penalty.","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-e1071","R-penalized","R-CRAN-recommended"]},{"type":"run","ports":["R"]}],"depends_on":[]},{"name":"R-missForest","portdir":"R/R-missForest","version":"1.5","license":"(GPL-2 or GPL-3)","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=missForest","description":"Non-parametric missing value imputation using random forest","long_description":"Non-parametric missing value imputation using random forest","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-randomForest","R-foreach","R-doRNG","R-CRAN-recommended","R-iterators","R-itertools"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-doParallel"]}],"depends_on":[{"type":"lib","ports":["R-longit"]}]},{"name":"R-missMDA","portdir":"R/R-missMDA","version":"1.19","license":"GPL-2+","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"http://factominer.free.fr/missMDA/index.html","description":"Handling of missing values with multivariate data analysis","long_description":"Handling of missing values with multivariate data analysis","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-doParallel","R-foreach","R-mice","R-FactoMineR","R-CRAN-recommended","R-mvtnorm","R-ggplot2"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-knitr","R-markdown"]}],"depends_on":[{"type":"lib","ports":["R-Factoshiny"]},{"type":"test","ports":["R-FactoMineR"]}]},{"name":"R-missSBM","portdir":"R/R-missSBM","version":"1.0.4","license":"GPL-3","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://grosssbm.github.io/missSBM","description":"Handling missing data in stochastic block models","long_description":"Handling missing data in stochastic block 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-RcppArmadillo","R-magrittr","R-rlang","R-ggplot2","R-future.apply","R-igraph","R-nloptr","R-RSpectra","R-CRAN-recommended","R-sbm","libgcc14","libgcc","R-R6","R-Rcpp"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-knitr","R-testthat","R-future","R-rmarkdown","R-covr","R-spelling","R-corrplot","R-aricode","R-blockmodels"]}],"depends_on":[]},{"name":"R-misspi","portdir":"R/R-misspi","version":"0.1.0","license":"GPL-2","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=misspi","description":"Missing value imputation in parallel","long_description":"Missing value imputation in parallel","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-foreach","R-plotly","R-glmnet","R-doSNOW","R-lightgbm","R-CRAN-recommended","R-SIS","R-ggplot2","R-doParallel"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-e1071","R-neuralnet"]}],"depends_on":[]},{"name":"R-mistr","portdir":"R/R-mistr","version":"0.0.6","license":"GPL-3","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=mistr","description":"Mixture and composite distributions","long_description":"Mixture and composite distributions","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-bbmle","R-CRAN-recommended"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-ggplot2","R-knitr","R-rmarkdown","R-pinp"]}],"depends_on":[{"type":"lib","ports":["R-evinf"]}]},{"name":"R-misty","portdir":"R/R-misty","version":"0.6.8","license":"MIT","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=misty","description":"Miscellaneous functions for descriptive statistics","long_description":"Miscellaneous functions for descriptive statistics","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-lavaan","R-lme4","R-haven","R-rstudioapi","R-CRAN-recommended","R-data.table","R-ggplot2"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-mnormt","R-plyr","R-readxl","R-patchwork","R-mice","R-writexl","R-hdf5r","R-mvnmle"]}],"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-19","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-mitools","portdir":"R/R-mitools","version":"2.4","license":"GPL-2","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=mitools","description":"Tools for multiple imputation of missing data","long_description":"Tools for multiple imputation of missing data","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-DBI","R-CRAN-recommended"]},{"type":"run","ports":["R"]}],"depends_on":[{"type":"lib","ports":["R-survey","R-relaimpo","R-kmi","R-miceadds","R-pan","R-psfmi"]},{"type":"test","ports":["R-lavaan.survey","R-medflex"]}]},{"name":"R-mix","portdir":"R/R-mix","version":"1.0-13","license":"Permissive","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=mix","description":"Estimation/multiple imputation programs for mixed categorical and continuous data","long_description":"Estimation/multiple imputation programs for mixed categorical and continuous data","active":true,"categories":["science","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":[{"type":"lib","ports":["R-LMest"]},{"type":"test","ports":["R-mclust"]}]},{"name":"R-mixAK","portdir":"R/R-mixAK","version":"5.8","license":"GPL-3+","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=mixAK","description":"Multivariate normal mixture models and mixtures of generalized linear mixed models including model-based clustering","long_description":"Multivariate normal mixture models and mixtures of generalized linear mixed models including model-based clustering","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-colorspace","R-lme4","R-fastGHQuad","R-CRAN-recommended","libgcc14","libgcc","R-mnormt","R-coda"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-mvtnorm"]}],"depends_on":[]},{"name":"R-mixOmics","portdir":"R/R-mixOmics","version":"6.28.0","license":"GPL-2+","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"http://www.mixOmics.org","description":"Omics Data Integration Project","long_description":"Omics Data Integration Project","active":true,"categories":["science","R","bioconductor"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-reshape2","R-tidyr","R-RColorBrewer","R-gridExtra","R-igraph","R-ggrepel","R-corpcor","R-ellipse","R-BiocParallel","R-rARPACK","R-CRAN-recommended","R-dplyr","R-matrixStats"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-knitr","R-testthat","R-rmarkdown","R-BiocStyle","R-rgl"]}],"depends_on":[{"type":"lib","ports":["R-xLLiM"]}]},{"name":"R-mixSPE","portdir":"R/R-mixSPE","version":"0.9.2","license":"GPL-2+","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=mixSPE","description":"Mixtures of power exponential and skew power exponential distributions for use in model-based clustering and classification","long_description":"Mixtures of power exponential and skew power exponential distributions for use in model-based clustering and classification","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"]},{"type":"test","ports":["R-testthat"]}],"depends_on":[]},{"name":"R-mixdist","portdir":"R/R-mixdist","version":"0.5-5","license":"(GPL-2 or GPL-3)","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=mixdist","description":"Finite Mixture Distribution models","long_description":"Finite Mixture Distribution models","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"]}]},{"name":"R-mixedClust","portdir":"R/R-mixedClust","version":"1.0.2","license":"GPL-2+","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=mixedClust","description":"Co-clustering of mixed type data","long_description":"Co-clustering of mixed type data","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-RcppProgress","R-fda","R-CRAN-recommended","libgcc14","libgcc","R-Rcpp","R-RcppArmadillo"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-knitr","R-rmarkdown","R-ordinalClust"]}],"depends_on":[]},{"name":"R-mixgb","portdir":"R/R-mixgb","version":"1.5.2","license":"GPL-3+","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://agnesdeng.github.io/mixgb","description":"Multiple imputation via xgboost","long_description":"Multiple imputation via xgboost","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-Rfast","R-data.table","R-magrittr","R-mice","R-xgboost","R-CRAN-recommended","libgcc14","libgcc","R-Rcpp","R-RcppArmadillo"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-knitr","R-rmarkdown"]}],"depends_on":[]},{"name":"R-mixl","portdir":"R/R-mixl","version":"1.3.4","license":"GPL-2+","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=mixl","description":"Simulated maximum likelihood estimation of mixed logit models for large datasets","long_description":"Simulated maximum likelihood estimation of mixed logit models for large datasets","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-sandwich","R-stringr","R-readr","R-randtoolbox","R-maxLik","R-CRAN-recommended","R-Rcpp","R-numDeriv"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-xtable","R-knitr","R-testthat","R-rmarkdown","R-texreg","R-mlogit"]}],"depends_on":[{"type":"test","ports":["R-logitr"]}]},{"name":"R-mixlm","portdir":"R/R-mixlm","version":"1.3.0","license":"GPL-2+","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=mixlm","description":"Mixed model ANOVA and statistics for education","long_description":"Mixed model ANOVA and statistics for education","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-leaps","R-multcomp","R-pls","R-CRAN-recommended","R-pracma","R-car"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-lme4"]}],"depends_on":[]},{"name":"R-mixmeta","portdir":"R/R-mixmeta","version":"1.2.0","license":"GPL-2+","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=mixmeta","description":"Extended mixed-effects framework for meta-analysis","long_description":"Extended mixed-effects framework for meta-analysis","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-mvmeta"]},{"type":"test","ports":["R-dlnm"]}]},{"name":"R-mixopt","portdir":"R/R-mixopt","version":"0.1.3","license":"LGPL-3+","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://github.com/CollinErickson/mixopt","description":"Mixed variable optimization","long_description":"Mixed variable optimization for non-linear functions.","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-splitfngr","R-CRAN-recommended","R-dplyr","R-ggplot2"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-gridExtra","R-testthat","R-lhs","R-ContourFunctions"]}],"depends_on":[]},{"name":"R-mixsmsn","portdir":"R/R-mixsmsn","version":"1.1-10","license":"GPL-2+","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=mixsmsn","description":"Fit a finite mixture of scale mixture of skew-normal distributions","long_description":"Fit a finite mixture of scale mixture of skew-normal 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":[{"type":"test","ports":["R-fmx"]}]},{"name":"R-mixsqp","portdir":"R/R-mixsqp","version":"0.3-54","license":"MIT","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=mixsqp","description":"Sequential quadratic programming for fast maximum-likelihood estimation of mixture proportions","long_description":"Sequential quadratic programming for fast maximum-likelihood estimation of mixture proportions","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-irlba","R-CRAN-recommended","libgcc14","libgcc","R-Rcpp","R-RcppArmadillo"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-knitr","R-testthat","R-rmarkdown"]}],"depends_on":[{"type":"lib","ports":["R-ashr","R-ebnm"]}]},{"name":"R-mixtools","portdir":"R/R-mixtools","version":"2.0.0","license":"(GPL-2 or GPL-3)","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://github.com/dsy109/mixtools","description":"Tools for analyzing finite mixture models","long_description":"Tools for analyzing finite mixture models","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-plotly","R-segmented","R-scales","R-CRAN-recommended","R-kernlab"]},{"type":"run","ports":["R"]}],"depends_on":[{"type":"lib","ports":["R-EntropyMCMC","R-MixSemiRob","R-RprobitB","R-ztpln"]},{"type":"test","ports":["R-Seurat","R-fmx"]}]},{"name":"R-mixture","portdir":"R/R-mixture","version":"2.1.1","license":"GPL-2+","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=mixture","description":"Mixture models for clustering and classification","long_description":"Mixture models for clustering and classification","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-Rcpp","R-RcppArmadillo","R-RcppGSL","libgcc","libgcc14","R-CRAN-recommended","gsl","R-BH"]},{"type":"run","ports":["R"]}],"depends_on":[{"type":"lib","ports":["R-Compositional","R-MixGHD"]}]},{"name":"R-mixvlmc","portdir":"R/R-mixvlmc","version":"0.2.1","license":"GPL-3+","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://fabrice-rossi.github.io/mixvlmc","description":"Variable length Markov chains with covariates","long_description":"Variable length Markov chains with covariates","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-rlang","R-stringr","R-withr","R-ggplot2","R-pROC","R-VGAM","R-butcher","R-CRAN-recommended","R-Rcpp","R-assertthat"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-data.table","R-tibble","R-knitr","R-testthat","R-waldo","R-rmarkdown","R-vdiffr","R-geodist"]}],"depends_on":[]},{"name":"R-mize","portdir":"R/R-mize","version":"0.2.4","license":"BSD","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://github.com/jlmelville/mize","description":"Unconstrained numerical optimization algorithms","long_description":"Unconstrained numerical optimization algorithms","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-ctsem"]}]},{"name":"R-mkde","portdir":"R/R-mkde","version":"0.3","license":"GPL-3+","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=mkde","description":"2D and 3D movement-based kernel density estimates (MKDEs)","long_description":"2D and 3D movement-based kernel density estimates (MKDEs)","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-sf","R-stars","R-Rcpp","R-CRAN-recommended","R-terra"]},{"type":"run","ports":["R"]}],"depends_on":[]},{"name":"R-mlVAR","portdir":"R/R-mlVAR","version":"0.5.2","license":"GPL-2","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=mlVAR","description":"Multi-level vector autoregression","long_description":"Multi-level vector autoregression","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-mvtnorm","R-plyr","R-dplyr","R-lme4","R-arm","R-corpcor","R-abind","R-MplusAutomation","R-clusterGeneration","R-graphicalVAR","R-CRAN-recommended","R-qgraph","R-rlang"]},{"type":"run","ports":["R"]}],"depends_on":[{"type":"lib","ports":["R-mnet"]}]},{"name":"R-mlapi","portdir":"R/R-mlapi","version":"0.1.1","license":"MIT","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=mlapi","description":"Abstract classes for building scikit-learn-ike API","long_description":"Abstract classes for building scikit-learn-ike API","active":true,"categories":["devel","science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-R6","R-CRAN-recommended"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-knitr"]}],"depends_on":[{"type":"lib","ports":["R-text2vec"]}]},{"name":"R-mlbench","portdir":"R/R-mlbench","version":"2.1-5","license":"GPL-2","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=mlbench","description":"Machine Learning Benchmark Problems","long_description":"Machine Learning Benchmark Problems","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-mlr3","R-bayesGAM"]},{"type":"test","ports":["R-Boruta","R-Cubist","R-Elja","R-bnclassify","R-bolasso","R-caret","R-caretEnsemble","R-clusterSim","R-dann","R-discrim","R-doParallel","R-doSNOW","R-e1071","R-ggparty","R-ipred","R-isotree","R-klaR","R-mboost","R-mlt.docreg","R-neighbr","R-nestedcv","R-party","R-partykit","R-pre","R-randomForestSRC","R-rbooster","R-sjtable2df","R-sparklyr","R-spikeSlabGAM","R-tidydann","R-tidyrules","R-tram","R-ATR","R-tramnet","R-BoomSpikeSlab"]}]},{"name":"R-mldr","portdir":"R/R-mldr","version":"0.4.3","license":"LGPL-3+","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=mldr","description":"Exploratory data analysis and manipulation of multi-label data sets","long_description":"Exploratory data analysis and manipulation of multi-label data sets","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-circlize","R-shiny","R-CRAN-recommended","R-XML"]},{"type":"run","ports":["R"]}],"depends_on":[]},{"name":"R-mlflow","portdir":"R/R-mlflow","version":"2.18.0","license":"Apache-2","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://mlflow.org","description":"Open-source platform for the machine learning lifecycle","long_description":"Open-source platform for the machine learning lifecycle","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-httpuv","R-jsonlite","R-rlang","R-glue","R-tibble","R-withr","R-processx","R-purrr","R-yaml","R-httr","R-ini","R-openssl","R-swagger","R-zeallot","R-forge","R-git2r","R-CRAN-recommended","R-base64enc","R-fs"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-stringi","R-testthat","R-covr","R-lintr","R-reticulate","R-xgboost","R-carrier","R-sparklyr"]}],"depends_on":[]},{"name":"R-mlegp","portdir":"R/R-mlegp","version":"3.1.9","license":"(GPL-2 or GPL-3)","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=mlegp","description":"Maximum Likelihood Estimates of Gaussian Processes","long_description":"Maximum Likelihood Estimates of Gaussian Processes","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-snowfall"]}],"depends_on":[{"type":"lib","ports":["R-TAG","R-c060","R-penalizedSVM"]},{"type":"test","ports":["R-ContourFunctions"]}]},{"name":"R-mlmRev","portdir":"R/R-mlmRev","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=mlmRev","description":"Examples from Multilevel Modelling Software Review","long_description":"Examples from Multilevel Modelling Software Review","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"]}],"depends_on":[{"type":"test","ports":["R-afex","R-clubSandwich","R-glmmEP","R-lme4","R-lmeInfo"]}]},{"name":"R-mlmc","portdir":"R/R-mlmc","version":"2.1.1","license":"GPL-2","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://mlmc.louisaslett.com","description":"Multi-Level Monte Carlo","long_description":"Multi-Level Monte Carlo","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-Rcpp","R-ggplot2","R-CRAN-recommended"]},{"type":"run","ports":["R"]}],"depends_on":[]},{"name":"R-mlogit","portdir":"R/R-mlogit","version":"1.1-1","license":"(GPL-2 or GPL-3)","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://r-forge.r-project.org/projects/mlogit","description":"Multinomial logit models","long_description":"Maximum likelihood estimation of random utility discrete choice models.","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-Formula","R-lmtest","R-Rdpack","R-dfidx","R-CRAN-recommended","R-statmod","R-zoo"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-ggplot2","R-knitr","R-rmarkdown","R-texreg","R-car","R-AER"]}],"depends_on":[{"type":"lib","ports":["R-gmnl","R-clusterSEs"]},{"type":"test","ports":["R-broom","R-insight","R-logitr","R-mixl","R-nonnest2","R-performance","R-prediction","R-AER","R-texreg","R-RprobitB"]}]},{"name":"R-mlmmm","portdir":"R/R-mlmmm","version":"0.3-1.2","license":"GPL-2","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=mlmmm","description":"ML estimation under multivariate linear mixed models with missing values","long_description":"ML estimation under multivariate linear mixed models with missing values","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-mlpack","portdir":"R/R-mlpack","version":"4.5.1","license":"BSD","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=mlpack","description":"Rcpp integration for the mlpack library","long_description":"A fast, flexible machine learning library, written in C++, that aims to provide fast, extensible implementations of cutting-edge machine learning algorithms.","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-RcppEnsmallen","R-CRAN-recommended","libgcc14","libgcc","R-Rcpp","R-RcppArmadillo"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-testthat"]}],"depends_on":[{"type":"test","ports":["R-genieclust"]}]},{"name":"R-mlr","portdir":"R/R-mlr","version":"2.19.2","license":"BSD","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://mlr.mlr-org.com","description":"Machine Learning in R","long_description":"Machine Learning in R","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-stringi","R-checkmate","R-ggplot2","R-BBmisc","R-XML","R-parallelMap","R-ParamHelpers","R-backports","R-CRAN-recommended","R-data.table"]},{"type":"run","ports":["gdal","R","gsl","jags","udunits","mpfr","gmp"]}],"depends_on":[{"type":"lib","ports":["R-mlrMBO","R-tramnet","R-varycoef"]},{"type":"test","ports":["R-bnclassify","R-plotmo"]}]},{"name":"R-mlr3","portdir":"R/R-mlr3","version":"0.21.0","license":"LGPL-3","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://mlr3.mlr-org.com","description":"Machine Learning in R","long_description":"Machine Learning in R – next generation.","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-data.table","R-evaluate","R-checkmate","R-future","R-future.apply","R-parallelly","R-uuid","R-mlbench","R-RhpcBLASctl","R-lgr","R-mlr3measures","R-mlr3misc","R-paradox","R-CRAN-recommended","R-palmerpenguins","R-R6","R-backports"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-remotes","R-progressr","R-callr","R-testthat","R-future.callr","R-mlr3data"]}],"depends_on":[{"type":"lib","ports":["R-mlr3tuning","R-mlr3learners","R-mlr3mbo","R-mlr3pipelines","R-mlr3resampling","R-mlr3superlearner"]},{"type":"test","ports":["R-vetiver","R-mlr3data"]}]},{"name":"R-mlr3data","portdir":"R/R-mlr3data","version":"0.7.0","license":"LGPL-3","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://github.com/mlr-org/mlr3data","description":"Collection of machine learning data-sets for R-mlr3","long_description":"Collection of machine learning data-sets for R-mlr3","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-mlr3"]}],"depends_on":[{"type":"test","ports":["R-mlr3","R-vetiver"]}]},{"name":"R-mlr3learners","portdir":"R/R-mlr3learners","version":"0.7.0","license":"LGPL-3","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://mlr3learners.mlr-org.com","description":"Recommended Learners for R-mlr3","long_description":"Recommended Learners for R-mlr3","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-CRAN-recommended","R-mlr3","R-R6","R-paradox","R-mlr3misc","R-data.table","R-checkmate"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-kknn","R-lgr","R-xgboost","R-e1071","R-knitr","R-testthat","R-rmarkdown","R-pracma","R-ranger","R-glmnet","R-DiceKriging","R-rgenoud"]}],"depends_on":[{"type":"lib","ports":["R-mlr3superlearner"]},{"type":"test","ports":["R-mlr3mbo","R-paradox","R-vetiver"]}]},{"name":"R-mlr3mbo","portdir":"R/R-mlr3mbo","version":"0.2.5","license":"LGPL-3","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://mlr3mbo.mlr-org.com","description":"Flexible Bayesian optimization","long_description":"Flexible Bayesian optimization","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-checkmate","R-lgr","R-spacefillr","R-mlr3misc","R-paradox","R-CRAN-recommended","R-mlr3","R-bbotk","R-mlr3tuning","R-R6","R-data.table"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-stringi","R-knitr","R-testthat","R-nloptr","R-rmarkdown","R-fastGHQuad","R-lhs","R-ranger","R-DiceKriging","R-rgenoud","R-emoa","R-mlr3learners","R-mlr3pipelines"]}],"depends_on":[]},{"name":"R-mlr3measures","portdir":"R/R-mlr3measures","version":"1.0.0","license":"LGPL-3","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://mlr3measures.mlr-org.com","description":"Performance measures for R-mlr3","long_description":"Performance measures for R-mlr3","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-PRROC","R-mlr3misc","R-CRAN-recommended","R-checkmate"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-testthat"]}],"depends_on":[{"type":"lib","ports":["R-mlr3"]}]},{"name":"R-mlr3misc","portdir":"R/R-mlr3misc","version":"0.15.1","license":"LGPL-3","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://mlr3misc.mlr-org.com","description":"Helper functions for R-mlr3","long_description":"Helper functions for R-mlr3","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-data.table","R-digest","R-checkmate","R-CRAN-recommended","R-R6","R-backports"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-evaluate","R-callr","R-testthat","R-paradox"]}],"depends_on":[{"type":"lib","ports":["R-bbotk","R-mlr3","R-mlr3learners","R-mlr3mbo","R-mlr3measures","R-mlr3pipelines","R-mlr3resampling","R-mlr3tuning","R-paradox"]},{"type":"test","ports":["R-usefun"]}]}]}