Pub Date : 2024-05-01DOI: 10.1080/00401706.2024.2339785
Vira Ananda, Visi Komala Sari, Anisah, Utriweni Mukhaiyar
Published in Technometrics (Vol. 66, No. 2, 2024)
发表于《技术计量学》（第 66 卷第 2 期，2024 年）
{"title":"Sparse Graphical Modeling for High Dimensional Data: A Paradigm of Conditional Independence Tests","authors":"Vira Ananda, Visi Komala Sari, Anisah, Utriweni Mukhaiyar","doi":"10.1080/00401706.2024.2339785","DOIUrl":"https://doi.org/10.1080/00401706.2024.2339785","url":null,"abstract":"Published in Technometrics (Vol. 66, No. 2, 2024)","PeriodicalId":22208,"journal":{"name":"Technometrics","volume":"55 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140833089","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 : 2024-04-19DOI: 10.1080/00401706.2024.2345139
Scott Koermer, Justin Loda, Aaron Noble, Robert B. Gramacy
The Kennedy and O’Hagan (KOH) calibration framework uses coupled Gaussian processes (GPs) to meta-model an expensive simulator (first GP), tune its “knobs” (calibration inputs) to best match observ...
{"title":"Augmenting a simulation campaign for hybrid computer model and field data experiments","authors":"Scott Koermer, Justin Loda, Aaron Noble, Robert B. Gramacy","doi":"10.1080/00401706.2024.2345139","DOIUrl":"https://doi.org/10.1080/00401706.2024.2345139","url":null,"abstract":"The Kennedy and O’Hagan (KOH) calibration framework uses coupled Gaussian processes (GPs) to meta-model an expensive simulator (first GP), tune its “knobs” (calibration inputs) to best match observ...","PeriodicalId":22208,"journal":{"name":"Technometrics","volume":"77 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140624127","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 : 2024-04-18DOI: 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":"19 1","pages":""},"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":"18 1","pages":""},"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":"1 1","pages":""},"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":"127 1","pages":""},"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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：