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"name": "R-clime",
"description": "Constrained L1-minimization for inverse (covariance) matrix estimation"
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{
"name": "R-clinfun",
"description": "Clinical trial design and data analysis functions"
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{
"name": "R-clipr",
"description": "Read and write from the system clipboard"
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{
"name": "R-clisymbols",
"description": "Unicode symbols for CLI applications, with fallbacks"
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{
"name": "R-clock",
"description": "Date–Time types and tools"
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{
"name": "R-clogitLasso",
"description": "Sparse conditional logistic regression for matched studies"
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{
"name": "R-cloudfs",
"description": "Streamlined interface to interact with cloud storage platforms"
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{
"name": "R-clpm",
"description": "Constrained estimation of linear probability model"
},
{
"name": "R-clubSandwich",
"description": "Cluster-robust (sandwich) variance estimators with small-sample corrections"
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{
"name": "R-clue",
"description": "Cluster Ensembles"
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{
"name": "R-clugenr",
"description": "Multi-dimensional cluster generation using support lines"
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{
"name": "R-ClusBoot",
"description": "Bootstrap a clustering solution to establish the stability of the clusters"
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{
"name": "R-cluscov",
"description": "Clustered covariate regression"
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{
"name": "R-ClusPred",
"description": "Simultaneous semi-parametric estimation of clustering and regression"
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{
"name": "R-clustAnalytics",
"description": "Cluster evaluation on graphs"
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{
"name": "R-clustComp",
"description": "Clustering Comparison"
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{
"name": "R-cluster",
"description": "Methods for cluster analysis"
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{
"name": "R-clusterGeneration",
"description": "Random cluster generation (with specified degree of separation)"
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{
"name": "R-clustermq",
"description": "Evaluate function calls on HPC schedulers"
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{
"name": "R-ClusterR",
"description": "Gaussian mixture models, k-means, mini-batch-kmeans, k-medoids and affinity propagation clustering"
},
{
"name": "R-clusterSEs",
"description": "Calculate cluster-robust p-values and confidence intervals"
},
{
"name": "R-clusterSim",
"description": "Search for an optimal clustering procedure for a data-set"
},
{
"name": "R-clustMixType",
"description": "k-prototypes clustering for mixed variable-type data"
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{
"name": "R-ClustOfVar",
"description": "Cluster analysis of a set of variables"
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{
"name": "R-clustRcompaR",
"description": "Easy interface for clustering a set of documents and exploring group-based patterns"
},
{
"name": "R-ClusVis",
"description": "Gaussian-based visualization of Gaussian and non-Gaussian model-based clustering"
},
{
"name": "R-clv",
"description": "Cluster validation techniques"
},
{
"name": "R-clValid",
"description": "Validation of clustering results"
},
{
"name": "R-cmaes",
"description": "Covariance Matrix Adapting Evolutionary Strategy"
},
{
"name": "R-CMAPSS",
"description": "Commercial Modular Aero-Propulsion System Simulation data-set"
},
{
"name": "R-cmdstanr",
"description": "R interface to CmdStan"
},
{
"name": "R-cml",
"description": "Conditional Manifold Learning"
},
{
"name": "R-CMLS",
"description": "Constrained Multivariate Least Squares"
},
{
"name": "R-cmm",
"description": "Categorical Marginal Models"
},
{
"name": "R-cmna",
"description": "Computational Methods for Numerical Analysis with R"
},
{
"name": "R-CMplot",
"description": "Circle Manhattan plot"
},
{
"name": "R-cmprsk",
"description": "Subdistribution analysis of competing risks"
},
{
"name": "R-cmvnorm",
"description": "Complex multivariate Gaussian distribution"
},
{
"name": "R-cnbdistr",
"description": "Conditional Negative Binomial Distribution"
},
{
"name": "R-cnum",
"description": "Chinese numerals processing"
},
{
"name": "R-CNVRG",
"description": "Dirichlet multinomial modelling of relative abundance data"
},
{
"name": "R-coalitions",
"description": "Bayesian now-cast estimation of event probabilities in multi-party democracies"
},
{
"name": "R-cobalt",
"description": "Covariate balance tables and plots"
},
{
"name": "R-cobs",
"description": "Qualitatively constrained (regression) smoothing splines via linear programming and sparse matrices"
},
{
"name": "R-coca",
"description": "Cluster-of-Clusters Analysis"
},
{
"name": "R-coconots",
"description": "Convolution-closed models for count time series"
},
{
"name": "R-cocor",
"description": "Statistical tests for the comparison between two correlations based on either independent or dependent groups"
},
{
"name": "R-cocosoR",
"description": "Combined Compromise Solution method for MCDA"
},
{
"name": "R-coda",
"description": "Output analysis and diagnostics for MCMC"
},
{
"name": "R-codalm",
"description": "Transformation-free linear regression for compositional outcomes and predictors"
}
]
}