Pub Date : 2024-04-18DOI: 10.1080/00401706.2024.2342314
Dongmin Li, Miao Bai, Xiaochen Xian
Moving vehicle-based sensors (MVSs) have been increasingly used for real-time sensing and anomaly detection in various applications such as the detection of wildfires and oil spills. In this paper,...
{"title":"Data-driven Pathwise Sampling Approaches for Online Anomaly Detection","authors":"Dongmin Li, Miao Bai, Xiaochen Xian","doi":"10.1080/00401706.2024.2342314","DOIUrl":"https://doi.org/10.1080/00401706.2024.2342314","url":null,"abstract":"Moving vehicle-based sensors (MVSs) have been increasingly used for real-time sensing and anomaly detection in various applications such as the detection of wildfires and oil spills. In this paper,...","PeriodicalId":22208,"journal":{"name":"Technometrics","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140615576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-16DOI: 10.1080/00401706.2024.2342315
Edward Austin, Idris A. Eckley, Lawrence Bardwell
Motivated by an example arising from digital networks, we propose a novel approach for detecting the emergence of anomalies in functional data. In contrast to classical functional data approaches, ...
{"title":"Detection of Emergent Anomalous Structure in Functional Data","authors":"Edward Austin, Idris A. Eckley, Lawrence Bardwell","doi":"10.1080/00401706.2024.2342315","DOIUrl":"https://doi.org/10.1080/00401706.2024.2342315","url":null,"abstract":"Motivated by an example arising from digital networks, we propose a novel approach for detecting the emergence of anomalies in functional data. In contrast to classical functional data approaches, ...","PeriodicalId":22208,"journal":{"name":"Technometrics","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140615577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-15DOI: 10.1080/00401706.2024.2343062
Sara Shashaani, Özge Sürer, Matthew Plumlee, Seth Guikema
Decision trees built with data remain in widespread use for nonparametric prediction. Predicting probability distributions is preferred over point predictions when uncertainty plays a prominent rol...
{"title":"Building Trees for Probabilistic Prediction via Scoring Rules","authors":"Sara Shashaani, Özge Sürer, Matthew Plumlee, Seth Guikema","doi":"10.1080/00401706.2024.2343062","DOIUrl":"https://doi.org/10.1080/00401706.2024.2343062","url":null,"abstract":"Decision trees built with data remain in widespread use for nonparametric prediction. Predicting probability distributions is preferred over point predictions when uncertainty plays a prominent rol...","PeriodicalId":22208,"journal":{"name":"Technometrics","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140583781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-28DOI: 10.1080/00401706.2024.2336535
Neelesh S Upadhye, Raju Chowdhury
In this article, we present a hybrid Bayesian optimization (BO) framework to solve constrained optimization problems by adopting a state-of-the-art acquisition function from the unconstrained BO li...
{"title":"Constrained Bayesian Optimization with Lower Confidence Bound","authors":"Neelesh S Upadhye, Raju Chowdhury","doi":"10.1080/00401706.2024.2336535","DOIUrl":"https://doi.org/10.1080/00401706.2024.2336535","url":null,"abstract":"In this article, we present a hybrid Bayesian optimization (BO) framework to solve constrained optimization problems by adopting a state-of-the-art acquisition function from the unconstrained BO li...","PeriodicalId":22208,"journal":{"name":"Technometrics","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140323846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-28DOI: 10.1080/00401706.2024.2336537
N. Fellmann, C. Blanchet-Scalliet, C. Helbert, A. Spagnol, D. Sinoquet
In this paper, we aim to perform sensitivity analysis of set-valued models and, in particular, to quantify the impact of uncertain inputs on feasible sets, which are key elements in solving a robus...
{"title":"Kernel-based Sensitivity Analysis for (excursion) sets","authors":"N. Fellmann, C. Blanchet-Scalliet, C. Helbert, A. Spagnol, D. Sinoquet","doi":"10.1080/00401706.2024.2336537","DOIUrl":"https://doi.org/10.1080/00401706.2024.2336537","url":null,"abstract":"In this paper, we aim to perform sensitivity analysis of set-valued models and, in particular, to quantify the impact of uncertain inputs on feasible sets, which are key elements in solving a robus...","PeriodicalId":22208,"journal":{"name":"Technometrics","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140584465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In recent years, diversified measurements reflect the system dynamics from a more comprehensive perspective in system modeling and analysis, such as scalars, waveform signals, images, and structure...
{"title":"Federated Multiple Tensor-on-Tensor Regression (FedMTOT) for Multimodal Data under Data-Sharing Constraints","authors":"Zihan Zhang, Shancong Mou, Mostafa Reisi Gahrooei, Massimo Pacella, Jianjun Shi","doi":"10.1080/00401706.2024.2333506","DOIUrl":"https://doi.org/10.1080/00401706.2024.2333506","url":null,"abstract":"In recent years, diversified measurements reflect the system dynamics from a more comprehensive perspective in system modeling and analysis, such as scalars, waveform signals, images, and structure...","PeriodicalId":22208,"journal":{"name":"Technometrics","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140314822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-13DOI: 10.1080/00401706.2024.2327341
Bianca M. Colosimo, L. Allison Jones-Farmer, Fadel M. Megahed, Kamran Paynabar, Chitta Ranjan, William H. Woodall
Industry 4.0 has emerged as an important era for process monitoring and improvement. Our expository paper provides a historical perspective on research and practice of statistical process monitorin...
{"title":"Statistical Process Monitoring from Industry 2.0 to Industry 4.0: Insights into Research and Practice","authors":"Bianca M. Colosimo, L. Allison Jones-Farmer, Fadel M. Megahed, Kamran Paynabar, Chitta Ranjan, William H. Woodall","doi":"10.1080/00401706.2024.2327341","DOIUrl":"https://doi.org/10.1080/00401706.2024.2327341","url":null,"abstract":"Industry 4.0 has emerged as an important era for process monitoring and improvement. Our expository paper provides a historical perspective on research and practice of statistical process monitorin...","PeriodicalId":22208,"journal":{"name":"Technometrics","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140170191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-07DOI: 10.1080/00401706.2024.2327346
Christian Capezza, Fabio Centofanti, Antonio Lepore, Biagio Palumbo
In modern Industry 4.0 applications, a huge amount of data is acquired during manufacturing processes and is often contaminated with outliers, which can seriously reduce the performance of control ...
{"title":"Robust Multivariate Functional Control Chart","authors":"Christian Capezza, Fabio Centofanti, Antonio Lepore, Biagio Palumbo","doi":"10.1080/00401706.2024.2327346","DOIUrl":"https://doi.org/10.1080/00401706.2024.2327346","url":null,"abstract":"In modern Industry 4.0 applications, a huge amount of data is acquired during manufacturing processes and is often contaminated with outliers, which can seriously reduce the performance of control ...","PeriodicalId":22208,"journal":{"name":"Technometrics","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140074175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-04DOI: 10.1080/00401706.2024.2321930
Sharmistha Guha, Rajarshi Guhaniyogi
This article focuses on model-based clustering of subjects based on the shared relationships of subject-specific networks and covariates in scenarios when there are differences in the relationship ...
本文的重点是在特定主体网络和协变量的共享关系存在差异的情况下，基于模型对主体进行聚类。
{"title":"Covariate-Dependent Clustering of Undirected Networks with Brain-Imaging Data","authors":"Sharmistha Guha, Rajarshi Guhaniyogi","doi":"10.1080/00401706.2024.2321930","DOIUrl":"https://doi.org/10.1080/00401706.2024.2321930","url":null,"abstract":"This article focuses on model-based clustering of subjects based on the shared relationships of subject-specific networks and covariates in scenarios when there are differences in the relationship ...","PeriodicalId":22208,"journal":{"name":"Technometrics","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140034715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-04DOI: 10.1080/00401706.2024.2322651
Tamara Dolski, Elaine T. Spiller, Susan E. Minkoff
Complex coupled multiphysics simulations are ubiquitous in science and engineering. Evaluating these numerical simulators is often costly which limits our ability to run them sufficiently often for...
{"title":"Gaussian Process Emulation for High-Dimensional Coupled Systems","authors":"Tamara Dolski, Elaine T. Spiller, Susan E. Minkoff","doi":"10.1080/00401706.2024.2322651","DOIUrl":"https://doi.org/10.1080/00401706.2024.2322651","url":null,"abstract":"Complex coupled multiphysics simulations are ubiquitous in science and engineering. Evaluating these numerical simulators is often costly which limits our ability to run them sufficiently often for...","PeriodicalId":22208,"journal":{"name":"Technometrics","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140034943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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