{"count":53082,"next":"https://ports.macports.org/api/v1/ports/?format=json&ordering=name&page=961","previous":"https://ports.macports.org/api/v1/ports/?format=json&ordering=name&page=959","results":[{"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":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","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":[]},{"name":"R-mirt","portdir":"R/R-mirt","version":"1.42","license":"GPL-3+","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://github.com/philchalmers/mirt/wiki","description":"Multidimensional Item Response Theory","long_description":"Multidimensional Item Response Theory","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-gridExtra","R-pbapply","R-Deriv","R-GPArotation","R-dcurver","R-vegan","R-CRAN-recommended","libgcc14","R-SimDesign","libgcc","R-Rcpp","R-RcppArmadillo"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-knitr","R-shiny","R-markdown","R-nloptr","R-latticeExtra","R-Rsolnp","R-plink","R-sirt","R-directlabels","R-mirtCAT"]}],"depends_on":[{"type":"lib","ports":["R-mirtCAT"]},{"type":"test","ports":["R-nonnest2","R-merDeriv","R-psychotree","R-rpf","R-sirt","R-psychotools"]}]},{"name":"R-mirtCAT","portdir":"R/R-mirtCAT","version":"1.14","license":"GPL-3+","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://github.com/philchalmers/mirtCAT/wiki","description":"Computerized adaptive testing with multidimensional item response theory","long_description":"R-mirtCAT provides tools to generate HTML interfaces for adaptive and non-adaptive tests using R-shiny package.","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-shiny","R-markdown","R-pbapply","R-lpSolve","R-mirt","R-CRAN-recommended","libgcc14","libgcc","R-Rcpp","R-RcppArmadillo"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-knitr","R-shinythemes"]}],"depends_on":[{"type":"test","ports":["R-mirt"]}]},{"name":"R-mirtjml","portdir":"R/R-mirtjml","version":"1.4.0","license":"GPL-3","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=mirtjml","description":"Joint maximum likelihood estimation for high-dimensional item factor analysis","long_description":"Joint maximum likelihood estimation for high-dimensional item factor analysis","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-GPArotation","R-CRAN-recommended","libgcc","libgcc14","R-Rcpp","R-RcppArmadillo"]},{"type":"run","ports":["R"]}],"depends_on":[{"type":"lib","ports":["R-mirtsvd"]}]},{"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-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-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-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-miWQS","portdir":"R/R-miWQS","version":"0.4.4","license":"GPL-3","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=miWQS","description":"Multiple imputation using weighted quantile sum regression","long_description":"Multiple imputation using weighted quantile sum regression","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-truncnorm","R-invgamma","R-purrr","R-tidyr","R-ggplot2","R-Hmisc","R-rlist","R-glm2","R-tmvtnorm","R-Rsolnp","R-MCMCpack","R-condMVNorm","R-matrixNormal","R-tmvmixnorm","R-CRAN-recommended","R-coda","R-mvtnorm"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-sessioninfo","R-knitr","R-scales","R-testthat","R-rmarkdown","R-spelling","R-GGally","R-formatR","R-mice","R-pander","R-norm","R-wqs"]}],"depends_on":[]},{"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-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-MixedPoisson","portdir":"R/R-MixedPoisson","version":"2.0","license":"GPL-2","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MixedPoisson","description":"Mixed Poisson models","long_description":"The estimation of the parameters in mixed Poisson models.","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-Rmpfr","R-gaussquad","R-CRAN-recommended"]},{"type":"run","ports":["R"]}],"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-MixGHD","portdir":"R/R-MixGHD","version":"2.3.7","license":"GPL-2+","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MixGHD","description":"Model-based clustering, classification and discriminant analysis","long_description":"Model-based clustering, classification and discriminant analysis using the mixture of generalized hyperbolic distributions.","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-numDeriv","R-Bessel","R-ghyp","R-e1071","R-CRAN-recommended","R-mixture","R-mvtnorm"]},{"type":"run","ports":["R"]}],"depends_on":[{"type":"lib","ports":["R-vscc"]}]},{"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-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-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-MixSemiRob","portdir":"R/R-MixSemiRob","version":"1.1.0","license":"GPL-2+","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MixSemiRob","description":"Mixture models: parametric, semiparametric and robust","long_description":"Mixture models: parametric, semiparametric and robust","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-quadprog","R-pracma","R-robustbase","R-mixtools","R-GoFKernel","R-Rlab","R-CRAN-recommended","R-mvtnorm","R-ucminf"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-knitr","R-rmarkdown"]}],"depends_on":[]},{"name":"R-MixSIAR","portdir":"R/R-MixSIAR","version":"3.1.12","license":"GPL-3","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://brianstock.github.io/MixSIAR","description":"Bayesian mixing models in R","long_description":"Bayesian mixing models in R","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-reshape","R-loo","R-reshape2","R-RColorBrewer","R-ggplot2","R-bayesplot","R-R2jags","R-MCMCpack","R-splancs","R-ggmcmc","R-CRAN-recommended","jags","R-coda"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-knitr","R-testthat","R-rmarkdown"]}],"depends_on":[]},{"name":"R-MixSim","portdir":"R/R-MixSim","version":"1.1-8","license":"GPL-2+","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MixSim","description":"Simulating data to study performance of clustering algorithms","long_description":"Simulating data to study performance of clustering 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":["libgcc","R-CRAN-recommended","libgcc14"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-mclust"]}],"depends_on":[{"type":"lib","ports":["R-SAGMM"]}]},{"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-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-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-MKLE","portdir":"R/R-MKLE","version":"1.0.1","license":"GPL","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MKLE","description":"Maximum Kernel Likelihood Estimation","long_description":"Maximum Kernel Likelihood Estimation","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-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-MLE","portdir":"R/R-MLE","version":"1.2","license":"GPL-2+","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MLE","description":"Maximum likelihood estimation of various univariate and multivariate distributions","long_description":"Maximum likelihood estimation of various univariate and multivariate distributions","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-skellam","R-BGFD","R-Directional","R-Compositional","R-CRAN-recommended","R-bivpois","R-gp","R-MN","R-geppe","R-Rfast","R-Rfast2"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-mvcauchy"]}],"depends_on":[]},{"name":"R-MLEce","portdir":"R/R-MLEce","version":"2.1.0","license":"GPL-2","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MLEce","description":"Asymptotic efficient closed-form estimators for multivariate distributions","long_description":"Asymptotic efficient closed-form estimators for multivariate distributions","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-ggplot2","R-nleqslv","R-LaplacesDemon","R-mvtnorm","R-CRAN-recommended","R-sirt","R-reshape"]},{"type":"run","ports":["R"]}],"depends_on":[]},{"name":"R-MLEcens","portdir":"R/R-MLEcens","version":"0.1-7.1","license":"GPL-2+","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MLEcens","description":"Computation of the MLE for bivariate interval censored data","long_description":"Computation of the MLE for bivariate interval censored 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-CRAN-recommended","libgcc14","libgcc"]},{"type":"run","ports":["R"]}],"depends_on":[{"type":"lib","ports":["R-icenReg","R-interval"]}]},{"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"]}]}]}