Clustering of bivariate satellite time series: a quantile approach

DOI10.1002/env.2755zbMATH Open1545.62881MaRDI QIDQ6626508

Victor Muthama Musau, Carlo Gaetan, Paolo Girardi

Publication date: 28 October 2024

Published in: Environmetrics (Search for Journal in Brave)

zbMATH Keywords

model-based clusteringquantile regressionwater qualityasymmetric Laplace distributiontrophic status

Mathematics Subject Classification ID

Applications of statistics to environmental and related topics (62P12)

Cites Work

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• Clusters of effects curves in quantile regression models
• Clustering Chlorophyll-a satellite data using quantiles
• Bayesian Lasso binary quantile regression
• Joint estimation of conditional quantiles in multivariate linear regression models with an application to financial distress
• Quantile-regression-based clustering for panel data
• A note on composite likelihood inference and model selection
• Regression Quantiles
• Finite mixture models
• Goodness of Fit and Related Inference Processes for Quantile Regression
• Bayesian Measures of Model Complexity and Fit
• Bayesian bivariate quantile regression
• Bayesian quantile regression
• Deviance information criteria for missing data models
• Spatially weighted functional clustering of river network data
• Hierarchical clustering of spatially correlated functional data

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