Robust distance measure to detect outliers for categorical data

DOI10.1007/s00500-019-04340-5OpenAlexW2975047950MaRDI QIDQ2156527

Yanyan Li

Publication date: 18 July 2022

Published in: Soft Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00500-019-04340-5

zbMATH Keywords

outliersdistance measurecategorical dataagglomerative linkage

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

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• Tucker3 Model for Compositional Data
• Clustering the rows and columns of a contingency table
• Outlier detection in contingency tables based on minimal patterns
• Visualizing categorical data in ViSta
• Classification of \(2\times 2\) sparse data sets with zero cells
• Unmasking outliers in two-way contingency tables.
• Outliers and Patterns of Outliers in Contingency Tables with Algebraic Statistics
• Identifying multiple influential observations in linear regression
• A Test for Detecting Outlying Cells in the Multinomial Distribution and Two-Way Contingency Tables
• Outlier Identification Procedures for Contingency Tables using Maximum Likelihood and L1 Estimates
• Theory & Methods: A Perturbation Approach to Outlier Detection in Two‐Way Contingency Tables
• Outlier detection for high dimensional data using the Comedian approach
• Discriminant partial least squares analysis on compositional data
• Contingency Table Analysis
• A Comparison of Different Methods for Representing Categorical Data

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