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Robust clustering based on trimming (Q6642753)

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scientific article; zbMATH DE number 7948875

Language	Label	Description	Also known as
English	Robust clustering based on trimming	scientific article; zbMATH DE number 7948875

Statements

scholarly article

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Robust clustering based on trimming (English)

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Luis A. García-Escudero

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Agustín Mayo-Iscar

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Wiley Interdisciplinary Reviews. WIREs Computational Statistics

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publication date

25 November 2024

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zbMATH Keywords

clustering

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model-based clustering

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robustness

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trimming

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MaRDI profile type

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Propagation of outliers in multivariate data

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Exploratory tools for clustering multivariate data

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Exploring multivariate data with the forward search.

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Cluster detection and clustering with random start forward searches

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Model-Based Gaussian and Non-Gaussian Clustering

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Robust and sparse \(k\)-means clustering for high-dimensional data

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Large-sample results for optimization-based clustering methods

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Graphical and Computational Tools to Guide Parameter Choice for the Cluster Weighted Robust Model

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A classification EM algorithm for clustering and two stochastic versions

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Wild adaptive trimming for robust estimation and cluster analysis

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Finding the Number of Normal Groups in Model-Based Clustering via Constrained Likelihoods

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Robust principal component analysis based on trimming around affine subspaces

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Impartial trimmed \(k\)-means for functional data

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Trimmed \(k\)-means: An attempt to robustify quantizers

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Trimmed best \(k\)-nets: A robustified version of an \(L_{\infty}\)-based clustering method

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Robust Estimation in the Normal Mixture Model Based on Robust Clustering

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Robust clustering tools based on optimal transportation

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Robust inference for parsimonious model-based clustering

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A reweighting approach to robust clustering

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Robust double clustering: a method based on alternating concentration steps

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Snipping for robust \(k\)-means clustering under component-wise contamination

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Robust model-based clustering with mild and gross outliers

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Soft clustering

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Co-clustering contaminated data: a robust model-based approach

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How Many Clusters? Which Clustering Method? Answers Via Model-Based Cluster Analysis

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A fast algorithm for robust constrained clustering

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Robust constrained fuzzy clustering

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A robust method for cluster analysis

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Trimming algorithms for clustering contaminated grouped data and their robustness

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Probabilistic clustering via Pareto solutions and significance tests

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Robustness Properties of k Means and Trimmed k Means

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A proposal for robust curve clustering

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The importance of the scales in heterogeneous robust clustering

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The joint role of trimming and constraints in robust estimation for mixtures of Gaussian factor analyzers

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Eigenvalues and constraints in mixture modeling: geometric and computational issues

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A general trimming approach to robust cluster analysis

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A review of robust clustering methods

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Exploring the number of groups in robust model-based clustering

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A constrained robust proposal for mixture modeling avoiding spurious solutions

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Robust clusterwise linear regression through trimming

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Robust Linear Clustering

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Model-based clustering with determinant-and-shape constraint

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Constrained parsimonious model-based clustering

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Cluster analysis with cellwise trimming and applications for the robust clustering of curves

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Outlier detection in the multiple cluster setting using the minimum covariance determinant estimator

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Clusters, outliers, and regression: Fixed point clusters

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Breakdown points for maximum likelihood estimators of location-scale mixtures

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How to find an appropriate clustering for mixed-type variables with application to socio-economic stratification

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A Cluster-Based Outlier Detection Scheme for Multivariate Data

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Least squares quantization in PCM

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Breakdown points of affine equivariant estimators of multivariate location and covariance matrices

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Robust Statistics

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Finite mixture models

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Robust fitting of mixtures using the trimmed likelihood estimator

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Parsimonious mixtures of multivariate contaminated normal distributions

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Robust clustering for functional data based on trimming and constraints

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Identification of Outliers in Multivariate Data

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The influence function of the TCLUST robust clustering procedure

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On the breakdown behavior of the TCLUST clustering procedure

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Model-Based Clustering, Classification, and Density Estimation Using mclust in R

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Root selection in normal mixture models

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Assessing trimming methodologies for clustering linear regression data

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Semiautomatic robust regression clustering of international trade data

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Robust mixture regression using the \(t\)-distribution

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Identifiers

zbMATH Open document ID

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10.1002/wics.1658

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Mathematics Subject Classification ID

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zbMATH DE Number

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Sitelinks

Mathematics(1 entry)

mardi Publication:6642753

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