Pages that link to "Item:Q65481"
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The following pages link to Estimating the number of clusters in a data set via the gap statistic (Q65481):
Displaying 50 items.
- Selection of variables in cluster analysis: An empirical comparison of eight procedures (Q946679) (← links)
- Clustering confidence sets (Q958762) (← links)
- Linear grouping using orthogonal regression (Q959227) (← links)
- A method of predicting the number of clusters using Rand's statistic (Q959433) (← links)
- Using combinatorial optimization in model-based trimmed clustering with cardinality constraints (Q962299) (← links)
- The Kullback information criterion for mixture regression models (Q968467) (← links)
- An integrative pathway-based clinical-genomic model for cancer survival prediction (Q988098) (← links)
- Dealing with label switching in mixture models under genuine multimodality (Q1006666) (← links)
- Online phenotype discovery based on minimum classification error model (Q1013370) (← links)
- CLUES: a non-parametric clustering method based on local shrinking (Q1020816) (← links)
- Assessing agreement of clustering methods with gene expression microarray data (Q1023916) (← links)
- Innovation in the cluster validating techniques (Q1028717) (← links)
- Statistical challenges in functional genomics. (With comments and a rejoinder). (Q1431220) (← links)
- A non-parametric method to estimate the number of clusters (Q1623424) (← links)
- Linearized alternating direction method of multipliers for sparse group and fused Lasso models (Q1623671) (← links)
- The cluster graphical Lasso for improved estimation of Gaussian graphical models (Q1623817) (← links)
- A divisive clustering method for functional data with special consideration of outliers (Q1630880) (← links)
- Spatial associations in global household bicycle ownership (Q1639260) (← links)
- Variable selection for high-dimensional genomic data with censored outcomes using group Lasso prior (Q1654247) (← links)
- Identification of relevant subtypes via preweighted sparse clustering (Q1658409) (← links)
- A simple approach to sparse clustering (Q1658539) (← links)
- Data filtering for cluster analysis by \(\ell _0\)-norm regularization (Q1686543) (← links)
- Variance-based cluster selection criteria in a \(K\)-means framework for one-mode dissimilarity data (Q1695625) (← links)
- Cluster analysis of longitudinal profiles with subgroups (Q1697471) (← links)
- Temporal clustering of time series via threshold autoregressive models: application to commodity prices (Q1703537) (← links)
- Clustering nonlinear, nonstationary time series using BSLEX (Q1707055) (← links)
- Multiscale blind source separation (Q1750285) (← links)
- Vector quantization of amino acids: Analysis of the HIV V3 loop region (Q1763453) (← links)
- Subject-treatment interactions in crossover trials: performance evaluation of subgrouping methods (Q1779795) (← links)
- Pattern layer reduction for a generalized regression neural network by using a self-organizing map (Q1784078) (← links)
- A quasi-Bayesian perspective to online clustering (Q1786586) (← links)
- A scalable solution framework for stochastic transmission and generation planning problems (Q1789560) (← links)
- Problems in gene clustering based on gene expression data (Q1876980) (← links)
- On a resampling approach for tests on the number of clusters with mixture model-based clustering of tissue samples (Q1876983) (← links)
- Finding predictive gene groups from microarray data (Q1876985) (← links)
- Regularized \(k\)-means clustering of high-dimensional data and its asymptotic consistency (Q1950809) (← links)
- Optimized profitability of LFP and NMC Li-ion batteries in residential PV applications (Q1998462) (← links)
- Likelihood ratio test for partial sphericity in high and ultra-high dimensions (Q2011514) (← links)
- Temporally consistent tone mapping of images and video using optimal \(K\)-means clustering (Q2014481) (← links)
- On the use of quantile regression to deal with heterogeneity: the case of multi-block data (Q2022484) (← links)
- A regionalisation approach for rainfall based on extremal dependence (Q2028583) (← links)
- Network modeling in biology: statistical methods for gene and brain networks (Q2038287) (← links)
- Optimality of spectral clustering in the Gaussian mixture model (Q2054516) (← links)
- Estimating the number of clusters in a ranking data context (Q2055574) (← links)
- On the behaviour of \(K\)-means clustering of a dissimilarity matrix by means of full multidimensional scaling (Q2066591) (← links)
- A graph clustering approach to localization for adaptive covariance tuning in data assimilation based on state-observation mapping (Q2066842) (← links)
- An empirical comparison between stochastic and deterministic centroid initialisation for K-means variations (Q2071340) (← links)
- K-bMOM: A robust Lloyd-type clustering algorithm based on bootstrap median-of-means (Q2072412) (← links)
- Temporal gap statistic: a new internal index to validate time series clustering (Q2128218) (← links)
- Partition of interval-valued observations using regression (Q2129302) (← links)
