{"count":53544,"next":"https://ports.macports.org/api/v1/ports/?format=json&ordering=updated_at&page=179","previous":"https://ports.macports.org/api/v1/ports/?format=json&ordering=updated_at&page=177","results":[{"name":"R-LatticeKrig","portdir":"R/R-LatticeKrig","version":"9.3.0","license":"GPL-2+","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=LatticeKrig","description":"Multi-resolution Kriging based on Markov random fields","long_description":"Multi-resolution Kriging based on Markov random fields","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-spam64","R-fftwtools","libgcc","libgcc14","R-CRAN-recommended","R-fields","R-spam"]},{"type":"run","ports":["R"]}],"depends_on":[{"type":"lib","ports":["R-autoFRK"]}]},{"name":"R-LearnBayes","portdir":"R/R-LearnBayes","version":"2.15.1","license":"GPL-2+","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=LearnBayes","description":"Functions for learning Bayesian inference","long_description":"Functions for learning Bayesian inference","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-ProbBayes","R-spatialreg"]}]},{"name":"R-LiblineaR","portdir":"R/R-LiblineaR","version":"2.10-24","license":"GPL-2","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://dnalytics.com/software/liblinear","description":"Linear predictive models based on the liblinear C/C++ library","long_description":"Linear predictive models based on the liblinear C/C++ library","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-SparseM"]}],"depends_on":[{"type":"lib","ports":["R-kebabs","R-quanteda.textmodels"]},{"type":"test","ports":["R-RSSL","R-parsnip","R-tidyAML","R-vetiver"]}]},{"name":"R-Lmoments","portdir":"R/R-Lmoments","version":"1.3-1","license":"GPL-2","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=Lmoments","description":"L-moments and quantile mixtures","long_description":"L-moments and quantile mixtures","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","libgcc","libgcc14","R-Rcpp","R-RcppArmadillo"]},{"type":"run","ports":["R"]}],"depends_on":[{"type":"lib","ports":["R-ROOPSD","R-extRemes","R-lmomco"]},{"type":"test","ports":["R-TLMoments"]}]},{"name":"R-LogicReg","portdir":"R/R-LogicReg","version":"1.6.6","license":"GPL-2+","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=LogicReg","description":"Logic Regression","long_description":"Logic Regression","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-LongMemoryTS","portdir":"R/R-LongMemoryTS","version":"0.1.0","license":"GPL-2","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=LongMemoryTS","description":"Long-memory time series","long_description":"Long-memory time series is a collection of functions for estimation, simulation and testing of long-memory processes, spurious long-memory processes and fractionally cointegrated systems.","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-mvtnorm","R-fracdiff","R-partitions","libgcc","R-CRAN-recommended","libgcc14","R-longmemo","R-Rcpp","R-RcppArmadillo"]},{"type":"run","ports":["R"]}],"depends_on":[{"type":"lib","ports":["R-memochange"]}]},{"name":"R-LorenzRegression","portdir":"R/R-LorenzRegression","version":"2.1.0","license":"GPL-3","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://github.com/AlJacq/LorenzRegression","description":"Lorenz and penalized Lorenz regressions","long_description":"Inference for the Lorenz and penalized Lorenz regressions. More broadly, the package proposes functions to assess inequality and graphically represent it.","active":true,"categories":["science","math","R","economics"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-ggplot2","R-knitr","R-scales","R-doParallel","R-foreach","R-GA","R-parsnip","R-rsample","R-locpol","R-Rearrangement","R-CRAN-recommended","R-Rcpp","R-RcppArmadillo"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-rmarkdown"]}],"depends_on":[]},{"name":"R-LowRankQP","portdir":"R/R-LowRankQP","version":"1.0.6","license":"GPL-2+","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=LowRankQP","description":"Low Rank Quadratic Programming","long_description":"Low Rank Quadratic Programming","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":"test","ports":["R-MSCMT"]}]},{"name":"R-MAPA","portdir":"R/R-MAPA","version":"2.0.7","license":"GPL-2+","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MAPA","description":"Multiple Aggregation Prediction Algorithm","long_description":"Multiple Aggregation Prediction Algorithm","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-smooth","R-RColorBrewer","R-CRAN-recommended","R-forecast"]},{"type":"run","ports":["R"]}],"depends_on":[{"type":"lib","ports":["R-tsutils"]}]},{"name":"R-MARSS","portdir":"R/R-MARSS","version":"3.11.9","license":"GPL-2","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://atsa-es.github.io/MARSS","description":"Multivariate Auto-Regressive State-Space modelling","long_description":"Multivariate Auto-Regressive State-Space modelling","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-KFAS","R-CRAN-recommended","R-mvtnorm","R-generics"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-ggplot2","R-knitr","R-forecast","R-Hmisc","R-marssTMB"]}],"depends_on":[{"type":"lib","ports":["R-marssTMB"]},{"type":"test","ports":["R-dsem","R-freqdom"]}]},{"name":"R-MASS","portdir":"R/R-MASS","version":"7.3-61","license":"(GPL-2 or GPL-3)","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MASS https://www.stats.ox.ac.uk/pub/MASS4","description":"Functions and datasets to support MASS (2002)","long_description":"Functions and datasets to support MASS (2002). Recommended package.","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-survival","R-lattice","R-nlme","R-nnet"]}],"depends_on":[{"type":"lib","ports":["R-class","R-CRAN-recommended"]},{"type":"test","ports":["R-KernSmooth","R-boot","R-cluster","R-mgcv","R-nlme","R-nnet","R-Matrix","R-spatial","R-lattice"]}]},{"name":"R-MAd","portdir":"R/R-MAd","version":"0.8-3","license":"GPL-2+","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MAd","description":"Meta-analysis with mean differences","long_description":"Meta-analysis with mean differences","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-ggplot2","R-metafor","R-CRAN-recommended"]},{"type":"run","ports":["R"]}],"depends_on":[{"type":"lib","ports":["R-RcmdrPlugin.MA"]}]},{"name":"R-MBA","portdir":"R/R-MBA","version":"0.1-2","license":"GPL-2+","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MBA","description":"Multilevel b-spline approximation","long_description":"Multilevel b-spline approximation","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-BH","R-CRAN-recommended"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-sp"]}],"depends_on":[{"type":"lib","ports":["R-bamlss","R-intamap"]},{"type":"test","ports":["R-R2BayesX","R-spBayes"]}]},{"name":"R-MBESS","portdir":"R/R-MBESS","version":"4.9.3","license":"(GPL-2 or GPL-3)","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://www3.nd.edu/~kkelley/site/MBESS.html","description":"The MBESS R package","long_description":"The MBESS R package","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-sem","R-semTools","R-OpenMx","R-CRAN-recommended","R-mnormt","R-lavaan"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-gsl"]}],"depends_on":[{"type":"lib","ports":["R-CoTiMA","R-fungible"]},{"type":"test","ports":["R-papaja","R-ufs"]}]},{"name":"R-MBSP","portdir":"R/R-MBSP","version":"4.0","license":"GPL-3","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MBSP","description":"Multivariate Bayesian model with shrinkage priors","long_description":"Multivariate Bayesian model with shrinkage priors","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-MCMCpack","R-mvtnorm","R-CRAN-recommended","R-GIGrvg"]},{"type":"run","ports":["R"]}],"depends_on":[{"type":"test","ports":["R-matrixNormal"]}]},{"name":"R-MCCM","portdir":"R/R-MCCM","version":"0.1.0","license":"GPL","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MCCM","description":"Mixed Correlation Coefficient Matrix","long_description":"Mixed Correlation Coefficient Matrix","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-lavaan","R-polycor","R-CRAN-recommended","R-mvtnorm"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-knitr","R-rmarkdown"]}],"depends_on":[]},{"name":"R-MCMCglmm","portdir":"R/R-MCMCglmm","version":"2.36","license":"GPL-2+","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://github.com/jarrodhadfield/MCMCglmm","description":"MCMC generalised linear mixed models","long_description":"MCMC generalised linear mixed models","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-cubature","R-tensorA","R-corpcor","R-CRAN-recommended","R-ape","R-coda"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-bayesm","R-mvtnorm","R-orthopolynom","R-MCMCpack","R-combinat","R-msm","R-rgl"]}],"depends_on":[{"type":"lib","ports":["R-StempCens","R-BayesMultiMode"]},{"type":"test","ports":["R-brms","R-broom.mixed","R-emmeans","R-ggeffects","R-insight","R-nadiv","R-tidybayes","R-MuMIn"]}]},{"name":"R-MCMCpack","portdir":"R/R-MCMCpack","version":"1.7-1","license":"GPL-3","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MCMCpack","description":"Markov Chain Monte Carlo (MCMC) package","long_description":"Markov Chain Monte Carlo (MCMC) package","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-mcmc","R-coda","R-CRAN-recommended","R-quantreg"]},{"type":"run","ports":["R"]}],"depends_on":[{"type":"lib","ports":["R-telescope","R-BMTAR","R-miWQS","R-mvst","R-prolsirm","R-robustsae","R-spikeSlabGAM","R-BMRMM","R-BayesESS","R-Bergm","R-DPtree","R-FAVAR","R-MBSP","R-MCPAN","R-MixSIAR","R-PLMIX","R-PRSPGx","R-RSGHB","R-bacr","R-bartcs","R-bayesanova","R-bayest","R-brxx","R-fungible","R-hdpGLM","R-llbayesireg","R-mHMMbayes","R-mbsts"]},{"type":"test","ports":["R-BayesDA","R-MCMCglmm","R-fido","R-pscl","R-dyn","R-emmeans"]}]},{"name":"R-MCMCprecision","portdir":"R/R-MCMCprecision","version":"0.4.0","license":"GPL-3","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MCMCprecision","description":"Precision of discrete parameters in transdimensional MCMC","long_description":"Precision of discrete parameters in transdimensional MCMC","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-RcppProgress","R-combinat","R-CRAN-recommended","libgcc14","libgcc","R-Rcpp","R-RcppArmadillo"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-testthat","R-R.rsp"]}],"depends_on":[]},{"name":"R-MCMCvis","portdir":"R/R-MCMCvis","version":"0.16.3","license":"GPL-3","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MCMCvis","description":"Tools to visualize, manipulate and summarize MCMC output","long_description":"Tools to visualize, manipulate and summarize MCMC output","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-rstan","R-overlapping","R-CRAN-recommended","R-coda","R-colorspace"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-knitr","R-testthat","R-posterior","R-rmarkdown","R-cmdstanr"]}],"depends_on":[]},{"name":"R-MCPAN","portdir":"R/R-MCPAN","version":"1.1-21","license":"GPL-2","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MCPAN","description":"Multiple contrast tests and simultaneous confidence intervals based on normal approximation","long_description":"Multiple contrast tests and simultaneous confidence intervals based on normal approximation","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-MCMCpack","R-magic","R-mvtnorm","R-CRAN-recommended","R-multcomp","R-plyr"]},{"type":"run","ports":["R"]}],"depends_on":[{"type":"lib","ports":["R-ANOM"]}]},{"name":"R-MDMR","portdir":"R/R-MDMR","version":"0.5.1","license":"GPL-2+","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://github.com/dmcartor/MDMR","description":"Multivariate Distance Matrix Regression","long_description":"Multivariate Distance Matrix Regression","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-lme4","R-car","R-CRAN-recommended","R-CompQuadForm"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-knitr","R-rmarkdown"]}],"depends_on":[]},{"name":"R-MEFM","portdir":"R/R-MEFM","version":"0.1.1","license":"GPL-3","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MEFM","description":"Perform MEFM estimation on matrix time series","long_description":"Perform MEFM estimation on matrix time series","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-CRAN-recommended","R-tensorMiss"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-rmarkdown","R-knitr"]}],"depends_on":[]},{"name":"R-MEMSS","portdir":"R/R-MEMSS","version":"0.9-3","license":"(GPL-2 or GPL-3)","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MEMSS","description":"Datasets from Mixed-Effects Models in S","long_description":"Datasets from Mixed-Effects Models in S","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-lme4","R-tidystats"]}]},{"name":"R-MFDFA","portdir":"R/R-MFDFA","version":"1.1","license":"GPL-3","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://mlaib.github.io","description":"Multi-Fractal Detrended Fluctuation Analysis","long_description":"Multi-Fractal Detrended Fluctuation Analysis","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-numbers","R-CRAN-recommended"]},{"type":"run","ports":["R"]}],"depends_on":[{"type":"test","ports":["R-fractalRegression"]}]},{"name":"R-MGMM","portdir":"R/R-MGMM","version":"1.0.1.1","license":"GPL-3","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MGMM","description":"Missingness-aware Gaussian Mixture Models","long_description":"Missingness-aware Gaussian Mixture 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-plyr","R-mvnfast","R-CRAN-recommended","libgcc14","libgcc","R-Rcpp","R-RcppArmadillo"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-withr","R-knitr","R-testthat","R-rmarkdown"]}],"depends_on":[]},{"name":"R-MHD","portdir":"R/R-MHD","version":"0.1.2","license":"GPL-2+","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MHD","description":"Metric Halfspace Depth","long_description":"Metric Halfspace Depth","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-nloptr","R-distory","R-manifold","R-CRAN-recommended","R-Rcpp","R-plyr"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-foreach"]}],"depends_on":[]},{"name":"R-MIIVsem","portdir":"R/R-MIIVsem","version":"0.5.8","license":"GPL-2","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MIIVsem","description":"Model Implied Instrumental Variable (MIIV) estimation of Structural Equation Models","long_description":"Model Implied Instrumental Variable (MIIV) estimation of Structural Equation Models","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-car","R-numDeriv","R-CRAN-recommended","R-lavaan"]},{"type":"run","ports":["R"]}],"depends_on":[{"type":"lib","ports":["R-gimme"]}]},{"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-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-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-MLmetrics","portdir":"R/R-MLmetrics","version":"1.1.3","license":"GPL-2","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://github.com/yanyachen/MLmetrics","description":"Machine learning evaluation metrics","long_description":"Machine learning evaluation metrics","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-ROCR","R-CRAN-recommended"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-e1071"]}],"depends_on":[{"type":"lib","ports":["R-daltoolbox","R-GroupBN","R-evinf","R-yager"]},{"type":"test","ports":["R-caret","R-cornet","R-isotree"]}]},{"name":"R-MM","portdir":"R/R-MM","version":"1.6-8","license":"GPL-2","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://github.com/RobinHankin/MM","description":"Multiplicative multinomial distribution","long_description":"Multiplicative multinomial distribution","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-mathjaxr","R-partitions","R-Oarray","R-abind","R-quadform","R-CRAN-recommended","R-magic"]},{"type":"run","ports":["R"]}],"depends_on":[]},{"name":"R-MMVBVS","portdir":"R/R-MMVBVS","version":"0.8.0","license":"GPL-2+","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MMVBVS","description":"Missing Multivariate Bayesian Variable Selection","long_description":"Missing Multivariate Bayesian Variable Selection","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-rlang","R-reshape","R-reshape2","R-ggplot2","R-CRAN-recommended","libgcc14","libgcc","R-Rcpp","R-RcppArmadillo"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-testthat"]}],"depends_on":[]},{"name":"R-MN","portdir":"R/R-MN","version":"1.0","license":"GPL-2+","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MN","description":"Matrix Normal Distribution","long_description":"Matrix Normal Distribution","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-Rfast","R-CRAN-recommended"]},{"type":"run","ports":["R"]}],"depends_on":[{"type":"lib","ports":["R-MLE"]}]},{"name":"R-MNP","portdir":"R/R-MNP","version":"3.1-5","license":"GPL-2+","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MNP","description":"Fitting the Multinomial Probit Model","long_description":"Fits the Bayesian multinomial probit model via Markov chain Monte Carlo.","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-testthat"]}],"depends_on":[{"type":"test","ports":["R-prediction"]}]},{"name":"R-MPV","portdir":"R/R-MPV","version":"1.64","license":"Permissive","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MPV","description":"Data Sets from Montgomery, Peck and Vining","long_description":"Data Sets from Montgomery, Peck and Vining","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-randomForest","R-CRAN-recommended"]},{"type":"run","ports":["R"]}],"depends_on":[{"type":"test","ports":["R-robustbase"]}]},{"name":"R-MPsychoR","portdir":"R/R-MPsychoR","version":"0.10-8","license":"GPL-2","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MPsychoR","description":"Modern Psychometrics with R","long_description":"Modern Psychometrics with R","active":true,"categories":["science","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-CRAN-recommended"]},{"type":"run","ports":["R"]}],"depends_on":[{"type":"test","ports":["R-smacof"]}]},{"name":"R-MRCE","portdir":"R/R-MRCE","version":"2.4","license":"GPL-2","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MRCE","description":"Multivariate Regression with Covariance Estimation","long_description":"Multivariate Regression with Covariance Estimation","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-glasso","R-CRAN-recommended"]},{"type":"run","ports":["R"]}],"depends_on":[{"type":"test","ports":["R-joinet"]}]},{"name":"R-MRFcov","portdir":"R/R-MRFcov","version":"1.0.39","license":"GPL-3","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://github.com/nicholasjclark/MRFcov","description":"Markov random fields with additional covariates","long_description":"Markov random fields with additional covariates","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-dplyr","R-purrr","R-reshape2","R-ggplot2","R-gridExtra","R-igraph","R-pbapply","R-sfsmisc","R-caret","R-glmnet","R-CRAN-recommended","R-magrittr","R-plyr"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-knitr","R-testthat","R-rmarkdown"]}],"depends_on":[]},{"name":"R-MSCMT","portdir":"R/R-MSCMT","version":"1.4.0","license":"GPL","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MSCMT","description":"Multivariate Synthetic Control Method using Time series","long_description":"Multivariate Synthetic Control Method using Time series","active":true,"categories":["science","R","economics"],"maintainers":[],"variants":["clang13","clang14","clang15","clang16","clang17","clang18","clang19","clangdevel","g95","gcc10","gcc11","gcc12","gcc13","gcc14","gccdevel","gfortran"],"dependencies":[{"type":"build","ports":["R","gcc14","clang-19"]},{"type":"lib","ports":["libgcc","libgcc14","R-CRAN-recommended","R-ggplot2","R-Rdpack","R-lpSolve","R-Rglpk","R-lpSolveAPI"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-NMOF","R-cmaes","R-soma","R-LowRankQP","R-Rmalschains","R-Synth","R-reshape","R-knitr","R-nloptr","R-rmarkdown","R-DEoptimR","R-GA","R-pso","R-kernlab","R-rgenoud","R-GenSA","R-DEoptim"]}],"depends_on":[]},{"name":"R-MSwM","portdir":"R/R-MSwM","version":"1.5","license":"(GPL-2 or GPL-3)","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MSwM","description":"Fitting Markov Switching Models","long_description":"Fitting Markov Switching 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":"test","ports":["R-LaMa","R-ggfortify","R-hmmTMB","R-tidyfit"]}]},{"name":"R-MTPS","portdir":"R/R-MTPS","version":"1.0.2","license":"GPL-2+","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MTPS","description":"Multi-task prediction using stacking algorithms","long_description":"Multi-task prediction using stacking algorithms","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-CRAN-recommended","R-e1071","R-glmnet"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-reshape2","R-ggplot2","R-knitr","R-rmarkdown"]}],"depends_on":[{"type":"test","ports":["R-joinet"]}]},{"name":"R-MTS","portdir":"R/R-MTS","version":"1.2.1","license":"Artistic-2","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MTS","description":"All-purpose toolkit for analyzing multivariate time series (MTS) and estimating multivariate volatility models","long_description":"All-purpose toolkit for analyzing multivariate time series (MTS) and estimating multivariate volatility models","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-mvtnorm","R-fBasics","R-Rcpp","R-CRAN-recommended","R-fGarch","R-RcppEigen"]},{"type":"run","ports":["R"]}],"depends_on":[{"type":"lib","ports":["R-VARDetect"]},{"type":"test","ports":["R-fable","R-tsBSS"]}]},{"name":"R-MTest","portdir":"R/R-MTest","version":"1.0.2","license":"GPL-3+","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MTest","description":"Procedure for multicollinearity testing using bootstrap","long_description":"Procedure for multicollinearity testing using bootstrap","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-plotly","R-ggplot2","R-CRAN-recommended","R-car"]},{"type":"run","ports":["R"]}],"depends_on":[]},{"name":"R-MVLM","portdir":"R/R-MVLM","version":"0.1.4","license":"GPL-2+","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MVLM","description":"Multivariate linear model with analytic p-values","long_description":"Multivariate linear model with analytic p-values","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["R","clang-19"]},{"type":"lib","ports":["R-CompQuadForm","R-CRAN-recommended"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-rmarkdown","R-knitr"]}],"depends_on":[]},{"name":"R-MXM","portdir":"R/R-MXM","version":"1.5.5","license":"GPL-2","platforms":"{darwin any}","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=MXM","description":"Feature selection and Bayesian networks","long_description":"Feature selection and Bayesian networks","active":true,"categories":["science","math","R"],"maintainers":[],"variants":[],"dependencies":[{"type":"build","ports":["clang-19","R"]},{"type":"lib","ports":["R-ordinal","R-dplyr","R-knitr","R-lme4","R-Hmisc","R-doParallel","R-foreach","R-quantreg","R-visNetwork","R-geepack","R-coxme","R-relations","R-energy","R-bigmemory","R-CRAN-recommended","R-Rfast","R-Rfast2"]},{"type":"run","ports":["R"]},{"type":"test","ports":["R-markdown","R-R.rsp"]}],"depends_on":[]},{"name":"R-ManlyMix","portdir":"R/R-ManlyMix","version":"0.1.15.1","license":"GPL-2+","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://cran.r-project.org/package=ManlyMix","description":"Manly mixture modeling and model-based clustering","long_description":"Manly mixture modeling and 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-CRAN-recommended","libgcc14","libgcc"]},{"type":"run","ports":["R"]}],"depends_on":[{"type":"lib","ports":["R-vscc"]}]}]}