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Large-Scale Low-Rank Gaussian Process Prediction with Support Points 带支持点的大规模低库高斯过程预测
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2024-09-20 DOI: 10.1080/01621459.2024.2403188
Yan Song, Wenlin Dai, Marc G. Genton
{"title":"Large-Scale Low-Rank Gaussian Process Prediction with Support Points","authors":"Yan Song, Wenlin Dai, Marc G. Genton","doi":"10.1080/01621459.2024.2403188","DOIUrl":"https://doi.org/10.1080/01621459.2024.2403188","url":null,"abstract":"Low-rank approximation is a popular strategy to tackle the “big n problem” associated with large-scale Gaussian process regressions. Basis functions for developing low-rank structures are crucial a...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"119 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142276069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Bisection Grover’s Search Algorithm and Its Application in Analyzing CITE-seq Data 分段格罗弗搜索算法及其在分析 CITE-seq 数据中的应用
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2024-09-20 DOI: 10.1080/01621459.2024.2404259
Ping Ma, Yongkai Chen, Haoran Lu, Wenxuan Zhong
{"title":"Bisection Grover’s Search Algorithm and Its Application in Analyzing CITE-seq Data","authors":"Ping Ma, Yongkai Chen, Haoran Lu, Wenxuan Zhong","doi":"10.1080/01621459.2024.2404259","DOIUrl":"https://doi.org/10.1080/01621459.2024.2404259","url":null,"abstract":"With the rapid development of quantum computers, researchers have shown quantum advantages in physics-oriented problems. Quantum algorithms tackling computational biology problems are still lacking...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"77 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142276068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Model-based clustering of categorical data based on the Hamming distance 基于汉明距离的分类数据模型聚类
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2024-09-20 DOI: 10.1080/01621459.2024.2402568
Raffaele Argiento, Edoardo Filippi-Mazzola, Lucia Paci
{"title":"Model-based clustering of categorical data based on the Hamming distance","authors":"Raffaele Argiento, Edoardo Filippi-Mazzola, Lucia Paci","doi":"10.1080/01621459.2024.2402568","DOIUrl":"https://doi.org/10.1080/01621459.2024.2402568","url":null,"abstract":"A model-based approach is developed for clustering categorical data with no natural ordering. The proposed method exploits the Hamming distance to define a family of probability mass functions to m...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"38 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142325564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
On Optimality of Mallows Model Averaging*† 论马洛模型平均化的最优性*†
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2024-09-20 DOI: 10.1080/01621459.2024.2402566
Jingfu Peng, Yang Li, Yuhong Yang
{"title":"On Optimality of Mallows Model Averaging*†","authors":"Jingfu Peng, Yang Li, Yuhong Yang","doi":"10.1080/01621459.2024.2402566","DOIUrl":"https://doi.org/10.1080/01621459.2024.2402566","url":null,"abstract":"In the past decades, model averaging (MA) has attracted much attention as it has emerged as an alternative tool to the model selection (MS) statistical approach. Hansen (2007) introduced a Mallows ...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"22 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142325359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Zigzag path connects two Monte Carlo samplers: Hamiltonian counterpart to a piecewise deterministic Markov process 连接两个蒙特卡罗采样器的之字形路径：与片断确定性马尔可夫过程相对应的哈密顿过程
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2024-09-18 DOI: 10.1080/01621459.2024.2395587
Akihiko Nishimura, Zhenyu Zhang, Marc A. Suchard
{"title":"Zigzag path connects two Monte Carlo samplers: Hamiltonian counterpart to a piecewise deterministic Markov process","authors":"Akihiko Nishimura, Zhenyu Zhang, Marc A. Suchard","doi":"10.1080/01621459.2024.2395587","DOIUrl":"https://doi.org/10.1080/01621459.2024.2395587","url":null,"abstract":"Zigzag and other piecewise deterministic Markov process samplers have attracted significant interest for their non-reversibility and other appealing properties for Bayesian posterior computation. H...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"15 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142245499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Valid Inference After Causal Discovery 因果发现后的有效推论
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2024-09-17 DOI: 10.1080/01621459.2024.2402089
Paula Gradu, Tijana Zrnic, Yixin Wang, Michael I. Jordan
{"title":"Valid Inference After Causal Discovery","authors":"Paula Gradu, Tijana Zrnic, Yixin Wang, Michael I. Jordan","doi":"10.1080/01621459.2024.2402089","DOIUrl":"https://doi.org/10.1080/01621459.2024.2402089","url":null,"abstract":"Causal discovery and causal effect estimation are two fundamental tasks in causal inference. While many methods have been developed for each task individually, statistical challenges arise when app...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"11 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142245501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Improving tensor regression by optimal model averaging 通过优化模型平均改进张量回归
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2024-09-13 DOI: 10.1080/01621459.2024.2398164
Qiushi Bu, Hua Liang, Xinyu Zhang, Jiahui Zou
{"title":"Improving tensor regression by optimal model averaging","authors":"Qiushi Bu, Hua Liang, Xinyu Zhang, Jiahui Zou","doi":"10.1080/01621459.2024.2398164","DOIUrl":"https://doi.org/10.1080/01621459.2024.2398164","url":null,"abstract":"Tensors have broad applications in neuroimaging, data mining, digital marketing, etc. CANDECOMP/PARAFAC (CP) tensor decomposition can effectively reduce the number of parameters to gain dimensional...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"30 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142317729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Off-policy Evaluation in Doubly Inhomogeneous Environments 双非均质环境中的非政策评估
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2024-09-09 DOI: 10.1080/01621459.2024.2395593
Zeyu Bian, Chengchun Shi, Zhengling Qi, Lan Wang
{"title":"Off-policy Evaluation in Doubly Inhomogeneous Environments","authors":"Zeyu Bian, Chengchun Shi, Zhengling Qi, Lan Wang","doi":"10.1080/01621459.2024.2395593","DOIUrl":"https://doi.org/10.1080/01621459.2024.2395593","url":null,"abstract":"This work aims to study off-policy evaluation (OPE) under scenarios where two key reinforcement learning (RL) assumptions – temporal stationarity and individual homogeneity are both violated. To ha...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"25 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142170863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Evaluating Treatment Prioritization Rules via Rank-Weighted Average Treatment Effects 通过加权平均治疗效果评估治疗优先级规则
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2024-09-03 DOI: 10.1080/01621459.2024.2393466
Steve Yadlowsky, Scott Fleming, Nigam Shah, Emma Brunskill, Stefan Wager
{"title":"Evaluating Treatment Prioritization Rules via Rank-Weighted Average Treatment Effects","authors":"Steve Yadlowsky, Scott Fleming, Nigam Shah, Emma Brunskill, Stefan Wager","doi":"10.1080/01621459.2024.2393466","DOIUrl":"https://doi.org/10.1080/01621459.2024.2393466","url":null,"abstract":"There are a number of available methods for selecting whom to prioritize for treatment, including ones based on treatment effect estimation, risk scoring, and hand-crafted rules. We propose rank-we...","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"50 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142245503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Models for Multi-State Survival Data: Rates, Risks, and Pseudo-Values 多州生存数据模型：比率、风险和伪值
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2024-08-30 DOI: 10.1080/01621459.2024.2395590
Ross L. Prentice
{"title":"Models for Multi-State Survival Data: Rates, Risks, and Pseudo-Values","authors":"Ross L. Prentice","doi":"10.1080/01621459.2024.2395590","DOIUrl":"https://doi.org/10.1080/01621459.2024.2395590","url":null,"abstract":"Published in Journal of the American Statistical Association (Just accepted, 2024)","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"104 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142170462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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