Analysis of spike train data: an application of \(k\)-mean alignment

DOI10.1214/14-EJS865AzbMath1305.62331WikidataQ62109461 ScholiaQ62109461MaRDI QIDQ470451

Laura M. Sangalli, Simone Vantini, Mirco Patriarca, Piercesare Secchi

Publication date: 12 November 2014

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.ejs/1414588161

zbMATH Keywords

registrationspike trainsfunctional clustering\(k\)-mean alignment

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Inference from stochastic processes and spectral analysis (62M15)

Related Items (4)

Analysis of spike train data: an application of \(k\)-mean alignment ⋮ Analysis of spike train data: discussion of results ⋮ Analysis of juggling data: an application of \(k\)-mean alignment ⋮ Analysis of AneuRisk65 data: \(k\)-mean alignment

Uses Software

• fdakma
• AneuRisk65

Cites Work

• Introduction to neural spike train data for phase-amplitude analysis
• Analysis of spike train data: an application of \(k\)-mean alignment
• Analysis of spike train data: alignment and comparisons using the extended Fisher-Rao metric
• Analysis of spike train data: comparison between the real and the simulated data
• Analysis of AneuRisk65 data: \(k\)-mean alignment
• \(k\)-mean alignment for curve clustering

This page was built for publication: Analysis of spike train data: an application of \(k\)-mean alignment