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"name": "R-mixsqp",
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"name": "R-mixtools",
"description": "Tools for analyzing finite mixture models"
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"name": "R-mixture",
"description": "Mixture models for clustering and classification"
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"name": "R-mixvlmc",
"description": "Variable length Markov chains with covariates"
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"name": "R-mize",
"description": "Unconstrained numerical optimization algorithms"
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"name": "R-mkde",
"description": "2D and 3D movement-based kernel density estimates (MKDEs)"
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"name": "R-MKLE",
"description": "Maximum Kernel Likelihood Estimation"
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{
"name": "R-mlapi",
"description": "Abstract classes for building scikit-learn-ike API"
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{
"name": "R-mlbench",
"description": "Machine Learning Benchmark Problems"
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{
"name": "R-mldr",
"description": "Exploratory data analysis and manipulation of multi-label data sets"
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{
"name": "R-MLE",
"description": "Maximum likelihood estimation of various univariate and multivariate distributions"
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{
"name": "R-MLEce",
"description": "Asymptotic efficient closed-form estimators for multivariate distributions"
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{
"name": "R-MLEcens",
"description": "Computation of the MLE for bivariate interval censored data"
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{
"name": "R-mlegp",
"description": "Maximum Likelihood Estimates of Gaussian Processes"
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{
"name": "R-mlflow",
"description": "Open-source platform for the machine learning lifecycle"
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"name": "R-mlmc",
"description": "Multi-Level Monte Carlo"
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"name": "R-MLmetrics",
"description": "Machine learning evaluation metrics"
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"name": "R-mlmmm",
"description": "ML estimation under multivariate linear mixed models with missing values"
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"name": "R-mlmRev",
"description": "Examples from Multilevel Modelling Software Review"
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{
"name": "R-mlogit",
"description": "Multinomial logit models"
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{
"name": "R-mlpack",
"description": "Rcpp integration for the mlpack library"
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{
"name": "R-mlr",
"description": "Machine Learning in R"
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"name": "R-mlr3",
"description": "Machine Learning in R"
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"name": "R-mlr3data",
"description": "Collection of machine learning data-sets for R-mlr3"
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"description": "Flexible Bayesian optimization"
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"description": "Performance measures for R-mlr3"
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"name": "R-mlr3misc",
"description": "Helper functions for R-mlr3"
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"name": "R-mlr3pipelines",
"description": "Preprocessing operators and pipelines for R-mlr3"
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"name": "R-mlr3resampling",
"description": "Resampling algorithms for R-mlr3"
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{
"name": "R-mlr3superlearner",
"description": "Super Learner fitting and prediction"
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{
"name": "R-mlr3tuning",
"description": "Hyperparameter optimization for R-mlr3"
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{
"name": "R-mlrMBO",
"description": "Bayesian optimization and model-based optimization of expensive black-box functions"
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{
"name": "R-mlsbm",
"description": "Efficient estimation of Bayesian SBMs & MLSBMs"
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{
"name": "R-mlt",
"description": "Most Likely Transformations"
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{
"name": "R-mlt.docreg",
"description": "Additional documentation, a package vignette and regression tests for R-mlt"
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{
"name": "R-mltools",
"description": "Machine Learning Tools"
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{
"name": "R-mlVAR",
"description": "Multi-level vector autoregression"
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{
"name": "R-MM",
"description": "Multiplicative multinomial distribution"
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{
"name": "R-mmand",
"description": "Mathematical Morphology in Any Number of Dimensions"
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{
"name": "R-mmapcharr",
"description": "Memory-map character files"
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{
"name": "R-mmcif",
"description": "Mixed Multivariate Cumulative Incidence Functions"
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{
"name": "R-mme",
"description": "Multinomial mixed effects models"
},
{
"name": "R-mmeln",
"description": "Estimation of multinormal mixture distribution"
},
{
"name": "R-mmpf",
"description": "Monte Carlo methods for prediction functions"
},
{
"name": "R-mmrm",
"description": "Mixed Models for Repeated Measures"
},
{
"name": "R-MMVBVS",
"description": "Missing Multivariate Bayesian Variable Selection"
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{
"name": "R-MN",
"description": "Matrix Normal Distribution"
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{
"name": "R-mnet",
"description": "Modelling group differences and moderation effects in statistical network models"
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{
"name": "R-mnonr",
"description": "Generator of multivariate non-normal random numbers"
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