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"name": "R-mirtsvd",
"description": "SVD-based estimation for exploratory item factor analysis"
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"name": "R-misc3d",
"description": "Collection of miscellaneous 3D plots, including isosurfaces"
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"description": "Variable selection for multiply imputed data"
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"name": "R-mispr",
"description": "Multiple Imputation with Sequential Penalized Regression"
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"name": "R-missForest",
"description": "Non-parametric missing value imputation using random forest"
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"name": "R-missMDA",
"description": "Handling of missing values with multivariate data analysis"
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"name": "R-misspi",
"description": "Missing value imputation in parallel"
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"name": "R-missSBM",
"description": "Handling missing data in stochastic block models"
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"name": "R-mistr",
"description": "Mixture and composite distributions"
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"name": "R-misty",
"description": "Miscellaneous functions for descriptive statistics"
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"name": "R-mitml",
"description": "Tools for multiple imputation in multi-level modelling"
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"name": "R-mitools",
"description": "Tools for multiple imputation of missing data"
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"name": "R-mixAK",
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"name": "R-mixdist",
"description": "Finite Mixture Distribution models"
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"name": "R-mixedClust",
"description": "Co-clustering of mixed type data"
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"description": "Mixed Poisson models"
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"name": "R-mixgb",
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"name": "R-MixGHD",
"description": "Model-based clustering, classification and discriminant analysis"
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"description": "Simulated maximum likelihood estimation of mixed logit models for large datasets"
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"name": "R-mixlm",
"description": "Mixed model ANOVA and statistics for education"
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"description": "Extended mixed-effects framework for meta-analysis"
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"name": "R-mixOmics",
"description": "Omics Data Integration Project"
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"name": "R-mixopt",
"description": "Mixed variable optimization"
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"name": "R-MixSemiRob",
"description": "Mixture models: parametric, semiparametric and robust"
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"name": "R-MixSIAR",
"description": "Bayesian mixing models in R"
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{
"name": "R-MixSim",
"description": "Simulating data to study performance of clustering algorithms"
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{
"name": "R-mixsmsn",
"description": "Fit a finite mixture of scale mixture of skew-normal distributions"
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"name": "R-mixSPE",
"description": "Mixtures of power exponential and skew power exponential distributions for use in model-based clustering and classification"
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"name": "R-mixsqp",
"description": "Sequential quadratic programming for fast maximum-likelihood estimation of mixture proportions"
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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"
},
{
"name": "R-MLEcens",
"description": "Computation of the MLE for bivariate interval censored data"
},
{
"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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}