A scale space approach for exploring structure in spherical data

DOI10.1016/j.csda.2018.03.014zbMath1469.62156OpenAlexW2795746194MaRDI QIDQ1662924

Lasse Holmström, Ville Vuollo

Publication date: 20 August 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2018.03.014

zbMATH Keywords

SiZerkernel density estimationscale spacespherical datadirectional statistics3D surface imaging

Mathematics Subject Classification ID

Directional data; spatial statistics (62H11) Computational methods for problems pertaining to statistics (62-08) Density estimation (62G07) Image analysis in multivariate analysis (62H35) Seismology (including tsunami modeling), earthquakes (86A15)

Related Items (2)

Comments on: ``Recent advances in directional statistics ⋮ Recent advances in directional statistics

Uses Software

• KernSmooth
• bootstrap
• CircSiZer
• SiZer

Cites Work

• Kernel density estimation with spherical data
• Exact risk improvement of bandwidth selectors for kernel density estimation with directional data
• The circular SiZer, inferred persistence of shape parameters and application to early stem cell differentiation
• Estimation of level set trees using adaptive partitions
• Smoothing of Multivariate Data
• Statistical Analysis of Spherical Data
• SiZer for Exploration of Structures in Curves
• Advanced Distribution Theory for SiZer
• Statistical Scale Space Methods
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