On measures of dissimilarity between point patterns: Classification based on prototypes and multidimensional scaling

DOI10.1002/bimj.201300150zbMath1310.62117OpenAlexW2122505562WikidataQ38287071 ScholiaQ38287071MaRDI QIDQ5247919

Jonatan A. González, Frederic Paik Schoenberg, David M. Diez, Jorge Mateu, Weipeng Lu

Publication date: 27 April 2015

Published in: Biometrical Journal (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/bimj.201300150

zbMATH Keywords

classificationprototypesmultidimensional scalingpoint patterns\(K\)-functionspike-time distance

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Applications of statistics to social sciences (62P25)

Related Items (5)

On the classification problem for Poisson point processes ⋮ Assessing similarities between spatial point patterns with a siamese neural network discriminant model ⋮ On computing medians of marked point process data under edit distance ⋮ Statistical analysis of complex and spatially dependent data: a review of object oriented spatial statistics ⋮ Metrics and barycenters for point pattern data

Uses Software

• R
• spatial
• smacof
• ppMeasures

Cites Work

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• Kaplan-Meier estimators of distance distributions for spatial point processes
• Nonmetric multidimensional scaling. A numerical method
• Patterns in spatial point locations: Local indicators of spatial association in a minefield with clutter
• On Parameter Estimation and Goodness-of-Fit Testing for Spatial Point Patterns
• A class of hypothesis tests for one and two sample censored survival data
• Metric-space analysis of spike trains: theory, algorithms and application
• An Introduction to the Theory of Point Processes
• Statistical Inference for Spatial Processes

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