Non-stationary spatial covariance structure estimation in oversampled domains by cluster differences scaling with spatial constraints

DOI10.1007/s00477-006-0100-3zbMath1169.62095OpenAlexW2009781823MaRDI QIDQ841862

J. Fernando Vera, José M. Angulo, Rodrigo Macías

Publication date: 18 September 2009

Published in: Stochastic Environmental Research and Risk Assessment (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00477-006-0100-3

zbMATH Keywords

multidimensional scaling\(k\)-means clusteringnon-stationarityanalysis of dispersionspatiotemporal processes

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to environmental and related topics (62P12)

Related Items (9)

Cluster differences unfolding for two-way two-mode preference rating data ⋮ Variance-based cluster selection criteria in a \(K\)-means framework for one-mode dissimilarity data ⋮ A dual latent class unfolding model for two-way two-mode preference rating data ⋮ A latent class MDS model with spatial constraints for non-stationary spatial covariance estimation ⋮ On the non-reducibility of non-stationary correlation functions to stationary ones under a class of mean-operator transformations ⋮ Cluster Optimized Proximity Scaling ⋮ On the behaviour of \(K\)-means clustering of a dissimilarity matrix by means of full multidimensional scaling ⋮ A latent class multidimensional scaling model for two-way one-mode continuous rating dissimilarity data ⋮ Clustering and representation of time series. Application to dissimilarities based on divergences

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