All packages

· A · B · C · D · E · F · G · H · I · J · K · L · M · N · O · P · Q · R · S · T · U · V · W · X · Y · Z ·

clusterHD — 1.0.2

Tools for Clustering High-Dimensional Data

Clustering — 1.7.10

Techniques for Evaluating Clustering

clustering.sc.dp — 1.1

Optimal Distance-Based Clustering for Multidimensional Data with Sequential Constraint

clusterMI — 1.2.2

Cluster Analysis with Missing Values by Multiple Imputation

clustermole — 1.1.1

Unbiased Single-Cell Transcriptomic Data Cell Type Identification

clustermq — 0.9.5

Evaluate Function Calls on HPC Schedulers (LSF, SGE, SLURM, PBS/Torque)

clusternomics — 0.1.1

Integrative Clustering for Heterogeneous Biomedical Datasets

ClusterR — 1.3.3

Gaussian Mixture Models, K-Means, Mini-Batch-Kmeans, K-Medoids and Affinity Propagation Clustering

ClusterRankTest — 1.0

Rank Tests for Clustered Data

clusterRepro — 0.9

Reproducibility of Gene Expression Clusters

clusterSEs — 2.6.5

Calculate Cluster-Robust p-Values and Confidence Intervals

clusterSim — 0.51-5

Searching for Optimal Clustering Procedure for a Data Set

ClusterStability — 1.0.4

Assessment of Stability of Individual Objects or Clusters in Partitioning Solutions

clustertend — 1.7

Check the Clustering Tendency

ClusterVAR — 0.0.7

Fitting Latent Class Vector-Autoregressive (VAR) Models

ClustGeo — 2.1

Hierarchical Clustering with Spatial Constraints

ClustImpute — 0.2.4

K-Means Clustering with Build-in Missing Data Imputation

clustlearn — 1.0.0

Learn Clustering Techniques Through Examples and Code

ClustMC — 0.1.1

Cluster-Based Multiple Comparisons

clustMD — 1.2.1

Model Based Clustering for Mixed Data

clustMixType — 0.4-2

k-Prototypes Clustering for Mixed Variable-Type Data

clustNet — 1.2.0

Network-Based Clustering

ClustOfVar — 1.1

Clustering of Variables

ClusTorus — 0.2.2

Prediction and Clustering on the Torus by Conformal Prediction

clustra — 0.2.1

Clustering Longitudinal Trajectories

clusTransition — 1.0

Monitor Changes in Cluster Solutions of Dynamic Datasets

clustrd — 1.4.0

Methods for Joint Dimension Reduction and Clustering

clustree — 0.5.1

Visualise Clusterings at Different Resolutions

clustringr — 1.0

Cluster Strings by Edit-Distance

CLUSTShiny — 0.1.0

Interactive Document for Working with Cluster Analysis

clustTMB — 0.1.0

Spatio-Temporal Finite Mixture Model using 'TMB'

ClustVarLV — 2.1.1

Clustering of Variables Around Latent Variables

clustvarsel — 2.3.4

Variable Selection for Gaussian Model-Based Clustering

ClusVis — 1.2.0

Gaussian-Based Visualization of Gaussian and Non-Gaussian Model-Based Clustering

clv — 0.3-2.4

Cluster Validation Techniques

clValid — 0.7

Validation of Clustering Results

CLVTools — 0.11.1

Tools for Customer Lifetime Value Estimation

cmaes — 1.0-12

Covariance Matrix Adapting Evolutionary Strategy

cmaesr — 1.0.3

Covariance Matrix Adaptation Evolution Strategy

cmahalanobis — 0.4.2

Calculate Distance Measures for a Given List of Data Frames with Factors

CMAPSS — 0.1.1

Commercial Modular Aero-Propulsion System Simulation Data Set

CMapViz — 0.1.0

Representation Tool For Output Of Connectivity Map (CMap) Analysis

cmaRs — 0.1.3

Implementation of the Conic Multivariate Adaptive Regression Splines in R

cmbClust — 0.0.1

Conditional Mixture Modeling and Model-Based Clustering

cmce — 0.1.0

Computer Model Calibration for Deterministic and Stochastic Simulators

cmcR — 0.1.11

An Implementation of the 'Congruent Matching Cells' Method

cmdfun — 1.0.2

Framework for Building Interfaces to Shell Commands

cmenet — 0.1.2

Bi-Level Selection of Conditional Main Effects

CMF — 1.0.3

Collective Matrix Factorization

cmfrec — 3.5.1-3

Collective Matrix Factorization for Recommender Systems

CMFsurrogate — 1.0

Calibrated Model Fusion Approach to Combine Surrogate Markers

CMGFM — 1.1

Covariate-Augumented Generalized Factor Model

cmhc — 0.2.9

Access, Retrieve, and Work with CMHC Data

CMHNPA — 1.1.1

Cochran-Mantel-Haenszel and Nonparametric ANOVA

cml — 0.2.2

Conditional Manifold Learning

CMLS — 1.0-1

Constrained Multivariate Least Squares

cmm — 1.0

Categorical Marginal Models

cmmr — 1.0.3

CEU Mass Mediator RESTful API

CMMs — 1.0.0

Compositional Mediation Model

cmna — 1.0.5

Computational Methods for Numerical Analysis

cmocean — 0.3-2

Beautiful Colour Maps for Oceanography

CMplot — 4.5.1

Circle Manhattan Plot

cmprsk — 2.2-12

Subdistribution Analysis of Competing Risks

cmprskcoxmsm — 0.2.1

Use IPW to Estimate Treatment Effect under Competing Risks

cmprskQR — 0.9.2

Analysis of Competing Risks Using Quantile Regressions

cmpsR — 0.1.2

R Implementation of Congruent Matching Profile Segments Method

cmR — 1.1

Analysis of Cardiac Magnetic Resonance Images

cmrutils — 1.3.1

Misc Functions of the Center for Mathematical Research

cms — 0.1.0

Calculate Medicare Reimbursement

cmsaf — 3.5.2

A Toolbox for CM SAF NetCDF Data

cmsafops — 1.4.0

Tools for CM SAF NetCDF Data

cmsafvis — 1.2.9

Tools to Visualize CM SAF NetCDF Data

CMShiny — 0.1.0

Interactive Document for Working with Confusion Matrix

cmstatr — 0.9.3

Statistical Methods for Composite Material Data

cmstatrExt — 0.4.0

More Statistical Methods for Composite Material Data

cmtest — 0.1-2

Conditional Moments Test

cmvnorm — 1.0-7

The Complex Multivariate Gaussian Distribution

cna — 3.6.2

Causal Modeling with Coincidence Analysis

CNAIM — 2.1.4

Common Network Asset Indices Methodology (CNAIM)

cnaOpt — 0.5.2

Optimizing Consistency and Coverage in Configurational Causal Modeling

cnbdistr — 1.0.1

Conditional Negative Binomial Distribution

cncaGUI — 1.1

Canonical Non-Symmetrical Correspondence Analysis in R

CNID — 1.3.1

Get Basic Information from Chinese ID Number

CNLTreg — 0.1-2

Complex-Valued Wavelet Lifting for Signal Denoising

CNLTtsa — 0.1-2

Complex-Valued Wavelet Lifting for Univariate and Bivariate Time Series Analysis

cnmap — 0.1.0

China Map Data from AutoNavi Map

cNORM — 3.4.0

Continuous Norming

CNprep — 2.2

Pre-Process DNA Copy Number (CN) Data for Detection of CN Events

CNPS — 1.0.0

Nonparametric Statistics

cnum — 0.1.3

Chinese Numerals Processing

CNVRG — 1.0.0

Dirichlet Multinomial Modeling of Relative Abundance Data

CNVScope — 3.7.2

A Versatile Toolkit for Copy Number Variation Relationship Data Analysis and Visualization

coala — 0.7.2

A Framework for Coalescent Simulation

coalescentMCMC — 0.4-4

MCMC Algorithms for the Coalescent

COAP — 1.2

High-Dimensional Covariate-Augmented Overdispersed Poisson Factor Model

coarseDataTools — 0.6-6

Analysis of Coarsely Observed Data

CoastlineFD — 1.1.2

Calculation of the Fractal Dimension of a Coastline

coat — 0.2.0

Conditional Method Agreement Trees (COAT)

cobalt — 4.5.5

Covariate Balance Tables and Plots

cobiclust — 0.1.2

Biclustering via Latent Block Model Adapted to Overdispersed Count Data

Next page