The quantile method for symbolic principal component analysis

DOI10.1002/sam.10111OpenAlexW2093506327MaRDI QIDQ4969760

Manabu Ichino

Publication date: 14 October 2020

Published in: Statistical Analysis and Data Mining: The ASA Data Science Journal (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/sam.10111

zbMATH Keywords

histogramquantilePCArank correlationmonotone structuresub-object

Mathematics Subject Classification ID

Statistics (62-XX) Computer science (68-XX)

Related Items (6)

Principal component analysis for histogram-valued data ⋮ Principal component analysis for probabilistic symbolic data: a more generic and accurate algorithm ⋮ New models for symbolic data analysis ⋮ Principal component histograms from interval-valued observations ⋮ Basic statistics for distributional symbolic variables: a new metric-based approach ⋮ Hierarchical conceptual clustering based on quantile method for identifying microscopic details in distributional data

Uses Software

• SODAS

Cites Work

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• Principal component analysis of interval data: a symbolic data analysis approach
• Symbolic Data Analysis
• Generalized Minkowski metrics for mixed feature-type data analysis
• Symbolic Data Analysis and the SODAS Software
• Analysis of symbolic data. Exploratory methods for extracting statistical information from complex data

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