Multi-feature clustering of step data using multivariate functional principal component analysis
From MaRDI portal
Publication:6579416
DOI10.1007/s00362-023-01467-4MaRDI QIDQ6579416
Wookyeong Song, Ying-Kuen Cheung, Yaeji Lim, Hee-Seok Oh
Publication date: 25 July 2024
Published in: Statistical Papers (Search for Journal in Brave)
Cites Work
- Estimating the Number of Clusters in a Data Set Via the Gap Statistic
- Simplicial principal component analysis for density functions in Bayes spaces
- Clustering multivariate functional data in group-specific functional subspaces
- The discriminative functional mixture model for a comparative analysis of bike sharing systems
- Estimation of density functions by order statistics
- Silhouettes: a graphical aid to the interpretation and validation of cluster analysis
- A practical guide to splines
- Model-based clustering for multivariate functional data
- Data driven orthogonal basis selection for functional data analysis
- Functional data clustering: a survey
- Functional data analysis.
- Joint modelling of paired sparse functional data using principal components
- Multivariate functional principal component analysis: A normalization approach
- Multi-class classification of biomechanical data: A functional LDA approach based on multi-class penalized functional PLS
- Sparse Functional Principal Component Analysis via Regularized Basis Expansions and Its Application
- Unsupervised Curve Clustering using B‐Splines
- Model-Based Clustering, Discriminant Analysis, and Density Estimation
- Principal component models for sparse functional data
- Multivariate Functional Principal Component Analysis for Data Observed on Different (Dimensional) Domains
- Functional Data Analysis for Sparse Longitudinal Data
- Functional data analysis for density functions by transformation to a Hilbert space
- Sparse multivariate functional principal component analysis
- Functional clustering of accelerometer data via transformed input variables
This page was built for publication: Multi-feature clustering of step data using multivariate functional principal component analysis