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Variational inference based on a subclass of closed skew normals 基于封闭偏斜法线子类的变量推理
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-09-12 DOI: 10.1080/10618600.2024.2402278
Linda S. L. Tan, Aoxiang Chen
{"title":"Variational inference based on a subclass of closed skew normals","authors":"Linda S. L. Tan, Aoxiang Chen","doi":"10.1080/10618600.2024.2402278","DOIUrl":"https://doi.org/10.1080/10618600.2024.2402278","url":null,"abstract":"Gaussian distributions are widely used in Bayesian variational inference to approximate intractable posterior densities, but the ability to accommodate skewness can improve approximation accuracy s...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142325075","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 nowcasting with Laplacian-P-splines 利用拉普拉斯-P-样条曲线进行贝叶斯现时预测
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-09-12 DOI: 10.1080/10618600.2024.2395414
Bryan Sumalinab, Oswaldo Gressani, Niel Hens, Christel Faes
{"title":"Bayesian nowcasting with Laplacian-P-splines","authors":"Bryan Sumalinab, Oswaldo Gressani, Niel Hens, Christel Faes","doi":"10.1080/10618600.2024.2395414","DOIUrl":"https://doi.org/10.1080/10618600.2024.2395414","url":null,"abstract":"During an epidemic, the daily number of reported infected cases, deaths or hospitalizations is often lower than the actual number due to reporting delays. Nowcasting aims to estimate the cases that...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142174598","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
Efficient convex PCA with applications to Wasserstein GPCA and ranked data 高效凸 PCA 与 Wasserstein GPCA 和排序数据的应用
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-09-12 DOI: 10.1080/10618600.2024.2402280
Steven Campbell, Ting-Kam Leonard Wong
{"title":"Efficient convex PCA with applications to Wasserstein GPCA and ranked data","authors":"Steven Campbell, Ting-Kam Leonard Wong","doi":"10.1080/10618600.2024.2402280","DOIUrl":"https://doi.org/10.1080/10618600.2024.2402280","url":null,"abstract":"Convex PCA, which was introduced in Bigot et al. (2017), modifies Euclidean PCA by restricting the data and the principal components to lie in a given convex subset of a Hilbert space. This setting...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142245216","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
Optimal decorrelated score subsampling for high-dimensional generalized linear models under measurement constraints 测量约束条件下高维广义线性模型的最优装饰相关得分子采样
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-09-12 DOI: 10.1080/10618600.2024.2402896
Yujing Shao, Lei Wang, Heng Lian
{"title":"Optimal decorrelated score subsampling for high-dimensional generalized linear models under measurement constraints","authors":"Yujing Shao, Lei Wang, Heng Lian","doi":"10.1080/10618600.2024.2402896","DOIUrl":"https://doi.org/10.1080/10618600.2024.2402896","url":null,"abstract":"When responses of massive data are hard to obtain due to some reasons such as privacy and security, high cost and administrative management, response-free subsampling is considered. In this paper, ...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142321119","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
Co-factor analysis of citation networks 引文网络的共因分析
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-08-27 DOI: 10.1080/10618600.2024.2394464
Alex Hayes, Karl Rohe
{"title":"Co-factor analysis of citation networks","authors":"Alex Hayes, Karl Rohe","doi":"10.1080/10618600.2024.2394464","DOIUrl":"https://doi.org/10.1080/10618600.2024.2394464","url":null,"abstract":"One compelling use of citation networks is to characterize papers by their relationships to the surrounding literature. We propose a method to characterize papers by embedding them into two distinc...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142130831","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 Bayesian Inference for Spatial Mean-Parameterized Conway–Maxwell–Poisson Models 空间均值参数化康威-麦克斯韦-泊松模型的快速贝叶斯推理
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-08-21 DOI: 10.1080/10618600.2024.2394460
Bokgyeong Kang, John Hughes, Murali Haran
{"title":"Fast Bayesian Inference for Spatial Mean-Parameterized Conway–Maxwell–Poisson Models","authors":"Bokgyeong Kang, John Hughes, Murali Haran","doi":"10.1080/10618600.2024.2394460","DOIUrl":"https://doi.org/10.1080/10618600.2024.2394460","url":null,"abstract":"Count data with complex features arise in many disciplines, including ecology, agriculture, criminology, medicine, and public health. Zero inflation, spatial dependence, and non-equidispersion are ...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142101054","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
Beyond time-homogeneity for continuous-time multistate Markov models 超越连续时间多态马尔可夫模型的时间同质性
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-08-08 DOI: 10.1080/10618600.2024.2388609
Emmett B. Kendall, Jonathan P. Williams, Gudmund H. Hermansen, Frederic Bois, Vo Hong Thanh
{"title":"Beyond time-homogeneity for continuous-time multistate Markov models","authors":"Emmett B. Kendall, Jonathan P. Williams, Gudmund H. Hermansen, Frederic Bois, Vo Hong Thanh","doi":"10.1080/10618600.2024.2388609","DOIUrl":"https://doi.org/10.1080/10618600.2024.2388609","url":null,"abstract":"Multistate Markov models are a canonical parametric approach for data modeling of observed or latent stochastic processes supported on a finite state space. Continuous-time Markov processes describ...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141909305","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
Degrees of Freedom: Search Cost and Self-consistency 自由度：搜索成本与自洽性
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-08-08 DOI: 10.1080/10618600.2024.2388545
Lijun Wang, Hongyu Zhao, Xiaodan Fan
{"title":"Degrees of Freedom: Search Cost and Self-consistency","authors":"Lijun Wang, Hongyu Zhao, Xiaodan Fan","doi":"10.1080/10618600.2024.2388545","DOIUrl":"https://doi.org/10.1080/10618600.2024.2388545","url":null,"abstract":"Model degrees of freedom ( df ) is a fundamental concept in statistics because it quantifies the flexibility of a fitting procedure and is indispensable in model selection. To investigate the gap b...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141915026","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
Scalable Estimation for Structured Additive Distributional Regression 结构化附加分布回归的可扩展估计
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-08-08 DOI: 10.1080/10618600.2024.2388604
Nikolaus Umlauf, Johannes Seiler, Mattias Wetscher, Thorsten Simon, Stefan Lang, Nadja Klein
{"title":"Scalable Estimation for Structured Additive Distributional Regression","authors":"Nikolaus Umlauf, Johannes Seiler, Mattias Wetscher, Thorsten Simon, Stefan Lang, Nadja Klein","doi":"10.1080/10618600.2024.2388604","DOIUrl":"https://doi.org/10.1080/10618600.2024.2388604","url":null,"abstract":"Obtaining probabilistic models is of high relevance in many recent applications. However, estimation of such distributional models with very large datasets remains a difficult task. In particular, ...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142130828","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 rejection sampling probability of acceptance as a measure of independence 用拒绝抽样的接受概率来衡量独立性
IF 2.4 2区 数学
Journal of Computational and Graphical Statistics Pub Date : 2024-08-06 DOI: 10.1080/10618600.2024.2388544
Markku Kuismin
{"title":"Using rejection sampling probability of acceptance as a measure of independence","authors":"Markku Kuismin","doi":"10.1080/10618600.2024.2388544","DOIUrl":"https://doi.org/10.1080/10618600.2024.2388544","url":null,"abstract":"This paper proposes a new association statistic for determining whether random variables are statistically independent. The proposed association statistic can also be used to examine the strength o...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141899847","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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