Analysis of spike train data: alignment and comparisons using the extended Fisher-Rao metric
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Publication:470452
DOI10.1214/14-EJS865BzbMath1305.62334OpenAlexW2051135208MaRDI QIDQ470452
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/1414588162
Applications of statistics to biology and medical sciences; meta analysis (62P10) Inference from stochastic processes and spectral analysis (62M15)
Related Items (9)
Amplitude and phase variation of point processes ⋮ Statistical inference on the Hilbert sphere with application to random densities ⋮ Bayesian semiparametric modelling of phase-varying point processes ⋮ Analysis of proteomics data: phase amplitude separation using an extended Fisher-Rao metric ⋮ Analysis of spike train data: an application of \(k\)-mean alignment ⋮ Analysis of spike train data: discussion of results ⋮ Analysis of AneuRisk65 data: \(k\)-mean alignment ⋮ Analysis of AneuRisk65 data: elastic shape registration of curves ⋮ A Spatial Modeling Approach for Linguistic Object Data: Analyzing Dialect Sound Variations Across Great Britain
Uses Software
Cites Work
- Generative models for functional data using phase and amplitude separation
- Analysis of proteomics data: phase amplitude separation using an extended Fisher-Rao metric
- Introduction to neural spike train data for phase-amplitude analysis
- Analysis of spike train data: classification and Bayesian alignment
- Analysis of spike train data: comparison between the real and the simulated data
- Functional data analysis.
- Pairwise curve synchronization for functional data
- Self-Modelling Warping Functions
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