Pesticide concentration monitoring: investigating spatio-temporal patterns in left censored data

DOI10.1002/ENV.2756zbMATH Open1545.62832MaRDI QIDQ6626557

Clément Laroche, Fabrice Rossi, Madalina Olteanu

Publication date: 28 October 2024

Published in: Environmetrics (Search for Journal in Brave)

zbMATH Keywords

Pareto frontanomaly detectionchange-point detectionwater pollutionleft censored datapesticide concentration monitoringprosulfocarb

Mathematics Subject Classification ID

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

Cites Work

• Title not available (Why is that?)
• Graph clustering
• Spatio-temporal change-point modeling
• Co-clustering of multivariate functional data for the analysis of air pollution in the south of France
• Detection and localization of change-points in high-dimensional network traffic data
• Detection of an anomalous cluster in a network
• Homogeneity and change-point detection tests for multivariate data using rank statistics
• Parametric Statistical Change Point Analysis
• Change-point detection, segmentation, and related topics
• Analysis of left censored data from the generalized exponential distribution
• The Structure and Function of Complex Networks
• Optimal Detection of Changepoints With a Linear Computational Cost
• S3T: A score statistic for spatiotemporal change point detection
• Optimal Transport
• Monitoring urban environmental pollution by bivariate control charts: new methodology and case study in Santiago, Chile

Related Items (3)

Environmental data science. II ⋮ Bayesian spatio-temporal survival analysis for all types of censoring with application to a wildlife disease study ⋮ Statistical evaluation of a long-memory process using the generalized entropic value-at-risk

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