Early identification of an impending rockslide location via a spatially-aided Gaussian mixture model

DOI10.1214/20-AOAS1326zbMath1446.62334OpenAlexW3037889708MaRDI QIDQ2194483

Yanyan Li

Publication date: 26 August 2020

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.aoas/1593449334

zbMATH Keywords

clusteringmixture modellandsliderockslide monitoring

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to environmental and related topics (62P12) Applications of statistics to physics (62P35) Geological problems (86A60)

Related Items (1)

A novel graph-theoretical clustering approach to find a reduced set with extreme solutions of Pareto optimal solutions for multi-objective optimization problems

Cites Work

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• Estimating the dimension of a model
• Investigation of parameter uncertainty in clustering using a Gaussian mixture model via jackknife, bootstrap and weighted likelihood bootstrap
• A Spatial Dirichlet Process Mixture Model for Clustering Population Genetics Data
• Model-Based Clustering, Discriminant Analysis, and Density Estimation

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