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Blocked Gibbs sampler for hierarchical Dirichlet processes 分层迪里希勒过程的阻塞吉布斯采样器
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-08-05 DOI: 10.1080/10618600.2024.2388543
Snigdha Das, Yabo Niu, Yang Ni, Bani K. Mallick, Debdeep Pati
{"title":"Blocked Gibbs sampler for hierarchical Dirichlet processes","authors":"Snigdha Das, Yabo Niu, Yang Ni, Bani K. Mallick, Debdeep Pati","doi":"10.1080/10618600.2024.2388543","DOIUrl":"https://doi.org/10.1080/10618600.2024.2388543","url":null,"abstract":"Posterior computation in hierarchical Dirichlet process (HDP) mixture models is an active area of research in nonparametric Bayes inference of grouped data. Existing literature almost exclusively f...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"300 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141899851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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
Augmentation Samplers for Multinomial Probit Bayesian Additive Regression Trees 多项式概率贝叶斯加性回归树的增量取样器
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-08-05 DOI: 10.1080/10618600.2024.2388605
Yizhen Xu, Joseph Hogan, Michael Daniels, Rami Kantor, Ann Mwangi
{"title":"Augmentation Samplers for Multinomial Probit Bayesian Additive Regression Trees","authors":"Yizhen Xu, Joseph Hogan, Michael Daniels, Rami Kantor, Ann Mwangi","doi":"10.1080/10618600.2024.2388605","DOIUrl":"https://doi.org/10.1080/10618600.2024.2388605","url":null,"abstract":"The multinomial probit (MNP) (Imai and van Dyk, 2005) framework is based on a multivariate Gaussian latent structure, allowing for natural extensions to multilevel modeling. Unlike multinomial logi...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"158 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141899848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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
Using early rejection Markov chain Monte Carlo and Gaussian processes to accelerate ABC methods 利用早期拒绝马尔科夫链蒙特卡洛和高斯过程加速 ABC 方法
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-07-15 DOI: 10.1080/10618600.2024.2379349
Xuefei Cao, Shijia Wang, Yongdao Zhou
{"title":"Using early rejection Markov chain Monte Carlo and Gaussian processes to accelerate ABC methods","authors":"Xuefei Cao, Shijia Wang, Yongdao Zhou","doi":"10.1080/10618600.2024.2379349","DOIUrl":"https://doi.org/10.1080/10618600.2024.2379349","url":null,"abstract":"Approximate Bayesian computation (ABC) is a class of Bayesian inference algorithms that targets problems with intractable or unavailable likelihood functions. It uses synthetic data drawn from the ...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"81 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141730633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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
Computational methods for fast Bayesian model assessment via calibrated posterior p-values 通过校准后p值快速评估贝叶斯模型的计算方法
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-07-11 DOI: 10.1080/10618600.2024.2374585
Sally Paganin, Perry de Valpine
{"title":"Computational methods for fast Bayesian model assessment via calibrated posterior p-values","authors":"Sally Paganin, Perry de Valpine","doi":"10.1080/10618600.2024.2374585","DOIUrl":"https://doi.org/10.1080/10618600.2024.2374585","url":null,"abstract":"Posterior predictive p-values (ppps) have become popular tools for Bayesian model assessment, being general-purpose and easy to use. However, interpretation can be difficult because their distribut...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"18 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141597631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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
Fast Computer Model Calibration using Annealed and Transformed Variational Inference 利用退火和变换变量推理进行快速计算机模型校准
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-07-08 DOI: 10.1080/10618600.2024.2374962
Dongkyu Derek Cho, Won Chang, Jaewoo Park
{"title":"Fast Computer Model Calibration using Annealed and Transformed Variational Inference","authors":"Dongkyu Derek Cho, Won Chang, Jaewoo Park","doi":"10.1080/10618600.2024.2374962","DOIUrl":"https://doi.org/10.1080/10618600.2024.2374962","url":null,"abstract":"Computer models play a crucial role in numerous scientific and engineering domains. To ensure the accuracy of simulations, it is essential to properly calibrate the input parameters of these models...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"28 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141584476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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
Functional Time Series Analysis and Visualization Based on Records 基于记录的功能时间序列分析和可视化
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-07-08 DOI: 10.1080/10618600.2024.2374578
Israel Martínez-Hernández, Marc G. Genton
{"title":"Functional Time Series Analysis and Visualization Based on Records","authors":"Israel Martínez-Hernández, Marc G. Genton","doi":"10.1080/10618600.2024.2374578","DOIUrl":"https://doi.org/10.1080/10618600.2024.2374578","url":null,"abstract":"In many phenomena, data are collected on a large scale and at different frequencies. In this context, functional data analysis (FDA) has become an important statistical methodology for analyzing an...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"25 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141557125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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
Stochastic Block Smooth Graphon Model 随机块平滑图模型
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-07-08 DOI: 10.1080/10618600.2024.2374571
Benjamin Sischka, Göran Kauermann
{"title":"Stochastic Block Smooth Graphon Model","authors":"Benjamin Sischka, Göran Kauermann","doi":"10.1080/10618600.2024.2374571","DOIUrl":"https://doi.org/10.1080/10618600.2024.2374571","url":null,"abstract":"In this paper, we propose combining the stochastic blockmodel and the smooth graphon model, two of the most prominent modeling approaches in statistical network analysis. Stochastic blockmodels are...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"40 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141597633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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
Continuous-time multivariate analysis 连续时间多元分析
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-07-08 DOI: 10.1080/10618600.2024.2374570
Biplab Paul, Philip T. Reiss, Erjia Cui, Noemi Foà
{"title":"Continuous-time multivariate analysis","authors":"Biplab Paul, Philip T. Reiss, Erjia Cui, Noemi Foà","doi":"10.1080/10618600.2024.2374570","DOIUrl":"https://doi.org/10.1080/10618600.2024.2374570","url":null,"abstract":"The starting point for much of multivariate analysis (MVA) is an n × p data matrix whose n rows represent observations and whose p columns represent variables. Some multivariate data sets, however,...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"20 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141597579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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
A Tidy Framework and Infrastructure to Systematically Assemble Spatio-temporal Indexes from Multivariate Data 从多变量数据中系统汇集时空索引的整洁框架和基础设施
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-07-08 DOI: 10.1080/10618600.2024.2374960
H. Sherry Zhang, Dianne Cook, Ursula Laa, Nicolas Langrené, Patricia Menéndez
{"title":"A Tidy Framework and Infrastructure to Systematically Assemble Spatio-temporal Indexes from Multivariate Data","authors":"H. Sherry Zhang, Dianne Cook, Ursula Laa, Nicolas Langrené, Patricia Menéndez","doi":"10.1080/10618600.2024.2374960","DOIUrl":"https://doi.org/10.1080/10618600.2024.2374960","url":null,"abstract":"Indexes are useful for summarizing multivariate information into single metrics for monitoring, communicating, and decision-making. While most work has focused on defining new indexes for specific ...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"153 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141597599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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
Dynamic prediction using landmark historical functional Cox regression 利用地标历史功能 Cox 回归进行动态预测
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-07-02 DOI: 10.1080/10618600.2024.2374576
Andrew Leroux, Ciprian Crainiceanu
{"title":"Dynamic prediction using landmark historical functional Cox regression","authors":"Andrew Leroux, Ciprian Crainiceanu","doi":"10.1080/10618600.2024.2374576","DOIUrl":"https://doi.org/10.1080/10618600.2024.2374576","url":null,"abstract":"Dynamic prediction of survival data in the presence of time-varying covariates is an area of active research. Two common analytic approaches for this type of data are joint modeling of the longitud...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"34 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141584477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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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