Showing entries 18101-18200 out of 52683.
Bootstrap a Clustering Solution to Establish the Stability of the Clusters
A Procedure for Cluster Evolution Analytics
Simultaneous Semi-Parametric Estimation of Clustering and Regression
Wilcoxon Rank Tests for Clustered Data
Simultaneous Detection of Clusters and Cluster-Specific Genes in High-Throughput Transcriptome Data
Cluster Evaluation on Graphs
Tools for Assessing Clustering
Clustering of Datasets
Identifying Similar T Cell Receptor Hyper-Variable Sequences with 'ClusTCR2'
Clustering Dose-Response Curves and Fitting Appropriate Models to Them
Clusters of Effects Curves in Quantile Regression Models
Performs Tests for Cluster Tendency of a Data Set
Analyze Clustered Data with Generalized Linear Models using the Cluster Bootstrap
Consensus Clustering using Multiple Algorithms and Parameters
Clustering Indices
Causal Effects from Observational Studies with Clustered Interference
Location and Visualization of Clustered Somatic Mutations
Random Cluster Generation (with Specified Degree of Separation)
Clustering Genotypes in Haplotypes
Tools for Clustering High-Dimensional Data
Techniques for Evaluating Clustering
Cluster Analysis with Missing Values by Multiple Imputation
Unbiased Single-Cell Transcriptomic Data Cell Type Identification
Evaluate Function Calls on HPC Schedulers (LSF, SGE, SLURM, PBS/Torque)
Integrative Clustering for Heterogeneous Biomedical Datasets
Gaussian Mixture Models, K-Means, Mini-Batch-Kmeans, K-Medoids and Affinity Propagation Clustering
Rank Tests for Clustered Data
Reproducibility of Gene Expression Clusters
Calculate Cluster-Robust p-Values and Confidence Intervals
Assessment of Stability of Individual Objects or Clusters in Partitioning Solutions
Check the Clustering Tendency
Fitting Latent Class Vector-Autoregressive (VAR) Models
Hierarchical Clustering with Spatial Constraints
K-Means Clustering with Build-in Missing Data Imputation
Learn Clustering Techniques Through Examples and Code
K-Prototypes Clustering for Mixed Variable-Type Data
Network-Based Clustering
Clustering of Variables
Prediction and Clustering on the Torus by Conformal Prediction
Monitor Changes in Cluster Solutions of Dynamic Datasets
Visualise Clusterings at Different Resolutions
Cluster Strings by Edit-Distance
Interactive Document for Working with Cluster Analysis
Clustering of Variables Around Latent Variables
Variable Selection for Gaussian Model-Based Clustering
Tools for Customer Lifetime Value Estimation
Calculate Distance Measures for a Given List of Data Frames with Factors
Conditional Mixture Modeling and Model-Based Clustering