Hierarchical multidimensional scaling for the comparison of musical performance styles

DOI10.1214/20-AOAS1391zbMath1485.62162arXiv2004.13870OpenAlexW3114919408MaRDI QIDQ2078727

Anna K. Yanchenko, Peter D. Hoff

Publication date: 3 March 2022

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2004.13870

zbMATH Keywords

Bayeshierarchical modelingfunctional datamultidimensional scalingaudio processing

Mathematics Subject Classification ID

Functional data analysis (62R10) Bayesian inference (62F15) Applications of statistics to psychology (62P15) One- and multidimensional scaling in the social and behavioral sciences (91C15)

Uses Software

• Stan
• BayesDA
• seewave
• RStan
• rstan
• t-SNE
• bmds
• WaveNet

Cites Work

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• A hierarchical Bayesian multidimensional scaling methodology for accommodating both structural and preference heterogeneity
• A Bayesian vector multidimensional scaling procedure incorporating dimension reparameterization with variable selection
• DISCO analysis: A nonparametric extension of analysis of variance
• Applied multidimensional scaling and unfolding
• Bayesian multidimensional scaling procedure with variable selection
• Analysis of individual differences in multidimensional scaling via an \(n\)-way generalization of ``Eckart-Young decomposition
• Multidimensional scaling. I: Theory and method
• An Overview of Sequence Comparison: Time Warps, String Edits, and Macromolecules
• Bayesian Multidimensional Scaling and Choice of Dimension
• Distance-based analysis of variance: Approximate inference
• Prior distributions for variance parameters in hierarchical models (Comment on article by Browne and Draper)

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