All packages

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ClinicalTrialSummary — 1.1.1

Summary Measures for Clinical Trials with Survival Outcomes

ClinicalUtilityRecal — 0.1.0

Recalibration Methods for Improved Clinical Utility of Risk Scores

clinmon — 0.6.0

Hemodynamic Calculations from Clinical Monitoring

clinPK — 0.13.0

Clinical Pharmacokinetics Toolkit

clinsig — 1.2

Clinical Significance Functions

ClinSigMeasures — 1.2

Clinical Significance Measures

clinspacy — 1.0.2

Clinical Natural Language Processing using 'spaCy', 'scispaCy', and 'medspaCy'

clintools — 0.9.10.1

Tools for Clinical Research

ClinTrialPredict — 0.0.4

Predicting and Simulating Clinical Trial with Time-to-Event Endpoint

clintrialx — 0.1.0

Connect and Work with Clinical Trials Data Sources

clinUtils — 0.2.0

General Utility Functions for Analysis of Clinical Data

cliot — 0.2.0

Clinical Indices and Outcomes Tools

clipp — 1.1.1

Calculating Likelihoods by Pedigree Paring

clipr — 0.8.0

Read and Write from the System Clipboard

CliquePercolation — 0.4.0

Clique Percolation for Networks

clisymbols — 1.2.0

Unicode Symbols at the R Prompt

CLME — 2.0-12

Constrained Inference for Linear Mixed Effects Models

clmplus — 1.0.0

Tool-Box of Chain Ladder Plus Models

clock — 0.7.1

Date-Time Types and Tools

clockify — 0.1.6

A Wrapper for the 'Clockify' API

clogitboost — 1.1

Boosting Conditional Logit Model

clogitL1 — 1.5

Fitting Exact Conditional Logistic Regression with Lasso and Elastic Net Penalties

cloneRate — 0.2.3

Estimate Growth Rates from Phylogenetic Trees

CloneSeeker — 1.0.11

Seeking and Finding Clones in Copy Number and Sequencing Data

CLONETv2 — 2.2.1

Clonality Estimates in Tumor

clordr — 1.7.0

Composite Likelihood Inference and Diagnostics for Replicated Spatial Ordinal Data

closeloop — 0.1.0

Integrate Single-Arm Observational Data in Network Meta Analysis

cloudfs — 0.1.3

Streamlined Interface to Interact with Cloud Storage Platforms

cloudml — 0.6.1

Interface to the Google Cloud Machine Learning Platform

cloudos — 0.4.0

R Client Library for CloudOS

cloudstoR — 0.2.0

Simplifies Access to Cloudstor API

cloudUtil — 0.1.12

Cloud Utilization Plots

clptheory — 0.1.0

Compute Price of Production and Labor Values

clr — 0.1.2

Curve Linear Regression via Dimension Reduction

clrng — 0.0.5

Parallel Random Number Generation on GPU

CLSIEP15 — 0.1.0

Clinical and Laboratory Standards Institute (CLSI) EP15-A3 Calculations

clttools — 1.3

Central Limit Theorem Experiments (Theoretical and Simulation)

clubpro — 0.6.2

Classification Using Binary Procrustes Rotation

clubSandwich — 0.5.11

Cluster-Robust (Sandwich) Variance Estimators with Small-Sample Corrections

clue — 0.3-66

Cluster Ensembles

ClueR — 1.4.2

Cluster Evaluation

clugenr — 1.0.3

Multidimensional Cluster Generation Using Support Lines

CluMP — 0.8.1

Clustering of Micro Panel Data

ClusBoot — 1.2.2

Bootstrap a Clustering Solution to Establish the Stability of the Clusters

cluscov — 1.1.0

Clustered Covariate Regression

clusEvol — 1.0.0

A Procedure for Cluster Evolution Analytics

ClusPred — 1.1.0

Simultaneous Semi-Parametric Estimation of Clustering and Regression

clusrank — 1.0-4

Wilcoxon Rank Tests for Clustered Data

ClusROC — 1.0.2

ROC Analysis in Three-Class Classification Problems for Clustered Data

ClussCluster — 0.1.0

Simultaneous Detection of Clusters and Cluster-Specific Genes in High-Throughput Transcriptome Data

clust.bin.pair — 0.1.2

Statistical Methods for Analyzing Clustered Matched Pair Data

clustAnalytics — 0.5.5

Cluster Evaluation on Graphs

ClustAssess — 0.3.0

Tools for Assessing Clustering

ClustBlock — 4.0.0

Clustering of Datasets

ClusTCR2 — 1.7.3.01

Identifying Similar T Cell Receptor Hyper-Variable Sequences with 'ClusTCR2'

clustcurv — 2.0.2

Determining Groups in Multiples Curves

clustEff — 0.3.1

Clusters of Effects Curves in Quantile Regression Models

cluster — 2.1.6

"Finding Groups in Data": Cluster Analysis Extended Rousseeuw et al.

cluster.datasets — 1.0-1

Cluster Analysis Data Sets

Cluster.OBeu — 1.2.3

Cluster Analysis 'OpenBudgets.eu'

clusterability — 0.1.1.0

Performs Tests for Cluster Tendency of a Data Set

ClusterBootstrap — 1.1.2

Analyze Clustered Data with Generalized Linear Models using the Cluster Bootstrap

clusterCrit — 1.3.0

Clustering Indices

ClusteredMutations — 1.0.1

Location and Visualization of Clustered Somatic Mutations

clusterGeneration — 1.3.8

Random Cluster Generation (with Specified Degree of Separation)

clusterhap — 0.1

Clustering Genotypes in Haplotypes

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'

clustur — 0.1.1

Clustering

ClustVarLV — 2.1.1

Clustering of Variables Around Latent Variables

clustvarsel — 2.3.4

Variable Selection for Gaussian Model-Based Clustering

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