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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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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
Bayesian Federated Learning with Hamiltonian Monte Carlo: Algorithm and Theory 哈密尔顿蒙特卡洛贝叶斯联合学习：算法与理论
IF 1.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-07-09 DOI: 10.1080/10618600.2024.2380051
Jiajun Liang, Qian Zhang, Wei Deng, Qifan Song, Guang Lin
{"title":"Bayesian Federated Learning with Hamiltonian Monte Carlo: Algorithm and Theory","authors":"Jiajun Liang, Qian Zhang, Wei Deng, Qifan Song, Guang Lin","doi":"10.1080/10618600.2024.2380051","DOIUrl":"https://doi.org/10.1080/10618600.2024.2380051","url":null,"abstract":"This work introduces a novel and efficient Bayesian federated learning algorithm, namely, the Federated Averaging stochastic Hamiltonian Monte Carlo (FA-HMC), for parameter estimation and uncertainty quantification. We establish rigorous convergence guarantees of FA-HMC on non-iid distributed data sets, under the strong convexity and Hessian smoothness assumptions. Our analysis investigates the effects of parameter space dimension, noise on gradients and momentum, and the frequency of communication (between the central node and local nodes) on the convergence and communication costs of FA-HMC. Beyond that, we establish the tightness of our analysis by showing that the convergence rate cannot be improved even for continuous FA-HMC process. Moreover, extensive empirical studies demonstrate that FA-HMC outperforms the existing Federated Averaging-Langevin Monte Carlo (FA-LD) algorithm.","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141663962","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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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
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