Journal of the American Statistical Association

最新文章

• Analyzing Whale Calling through Hawkes Process Modeling AI翻译
  作者：Kang, Bokgyeong; Schliep, Erin M.; Gelfand, Alan E.; Yack, Tina M.; Clark, Christopher W.; Schick, Robert S.
  作者单位：Duke University; Dongguk University; North Carolina State University; Duke University; Cornell University
  摘要：Sound is assumed to be the primary modality of communication among marine mammal species. Analyzing acoustic recordings helps to understand the function of the acoustic signals as well as the possible impact of anthropogenic noise on acoustic behavior. Motivated by a dataset from a network of hydrophones in Cape Cod Bay, Massachusetts, using automatically detected calls in recordings, we study the communication process of the endangered North Atlantic right whale. For right whales, an upcall i...
• Simultaneous Inference for Generalized Linear Models with Unmeasured Confounders AI翻译
  作者：Du, Jin-Hong; Wasserman, Larry; Roeder, Kathryn
  作者单位：Carnegie Mellon University; Carnegie Mellon University; Carnegie Mellon University
  摘要：Tens of thousands of simultaneous hypothesis tests are routinely performed in genomic studies to identify differentially expressed genes. However, due to unmeasured confounders, many standard statistical approaches may be substantially biased. This article investigates the large-scale hypothesis testing problem for multivariate generalized linear models in the presence of confounding effects. Under arbitrary confounding mechanisms, we propose a unified statistical estimation and inference fram...
• Prediction of Cognitive Function via Brain Region Volumes with Applications to Alzheimer's Disease Based on Space-Factor-Guided Functional Principal Component Analysis AI翻译
  作者：Wen, Shoudao; Li, Yi; Kong, Dehan; Lin, Huazhen
  作者单位：Southwestern University of Finance & Economics - China; Southwestern University of Finance & Economics - China; University of Michigan System; University of Michigan; University of Toronto
  摘要：Alzheimer's disease (AD) is a prevalent and irreversible brain disorder and early prediction of cognitive function is vital for detecting the onset. The volumes of brain regions can serve as features for predicting cognitive decline, facilitating early detection and intervention. In order to offer a comprehensive representation of brain tissue changes in AD, we employ volume density curves to investigate the relationship between brain regions and cognitive function. However, analyzing these vo...
• Frequency Domain Statistical Inference for High-Dimensional Time Series AI翻译
  作者：Krampe, Jonas; Paparoditis, Efstathios
  作者单位：Cornell University; University of Cyprus
  摘要：Analyzing time series in the frequency domain enables the development of powerful tools for investigating the second-order characteristics of multivariate processes. Parameters like the spectral density matrix and its inverse, the coherence or the partial coherence, encode comprehensively the complex linear relations between the component processes of the multivariate system. In this article, we develop inference procedures for such parameters in a high-dimensional, time series setup. Toward t...
• Discussion of Data Fission: Splitting a Single Data Point AI翻译
  作者：Neufeld, Anna; Dharamshi, Ameer; Gao, Lucy L.; Witten, Daniela; Bien, Jacob
  作者单位：Williams College; University of Washington; University of Washington Seattle; University of British Columbia; University of Washington; University of Washington Seattle; University of Washington; University of Washington Seattle; University of Southern California
• Saha and Ramdas' Discussion of Poisson-FOCuS by Ward, Dilillo, Eckley & Fearnhead AI翻译
  作者：Saha, Aytijhya; Ramdas, Aaditya
  作者单位：Indian Statistical Institute; Indian Statistical Institute Kolkata; Carnegie Mellon University
• Identifiability and Inference for Generalized Latent Factor Models AI翻译
  作者：Cui, Chengyu; Xu, Gongjun
  作者单位：University of Michigan System; University of Michigan
  摘要：Generalized latent factor analysis not only provides a useful latent embedding approach in statistics and machine learning, but also serves as a widely used tool across various scientific fields, such as psychometrics, econometrics, and social sciences. Ensuring the identifiability of latent factors and the loading matrix is essential for the model's estimability and interpretability, and various identifiability conditions have been employed by practitioners. However, fundamental statistical i...
• Investigating Spatial Dynamics in Spatial Omics Data with StarTrail AI翻译
  作者：Chen, Jiawen; Xiong, Caiwei; Sun, Quan; Song, Yutong; Wang, Geoffery W.; Gupta, Gaorav P.; Halder, Aritra; Li, Yun; Li, Didong
  作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine; University of Pennsylvania; Pennsylvania Medicine; Childrens Hospital of Philadelphia; University of Pennsylvania; Pennsylvania Medicine; Childrens Hospital of Philadelphia; University of Pennsylvania; Pennsylvania Medicine; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine; Drexel University; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine
  摘要：Spatial omics technologies revolutionize our view of biological processes within tissues. However, existing methods fail to capture localized, sharp changes characteristic of critical events (e.g., tumor development). Here, we present StarTrail, a novel gradient based method that powerfully defines rapidly changing regions and detects cliff genes, genes exhibiting drastic expression changes at highly localized or disjoint boundaries. StarTrail, the first to leverage spatial gradients for spati...
• Change Point Analysis: Theory and Application AI翻译
  作者：Kaul, Abhishek
  作者单位：Washington State University
• ℤ-Valued Smooth Transition GARCH Models: Specification and Testing AI翻译
  作者：Zhu, Fukang; Xu, Nuo; Li, Qi; Ling, Shiqing
  作者单位：Jilin University; Changchun Normal University; Hong Kong University of Science & Technology
  摘要：This article introduces a new class of nonlinear models known as the Z-valued smooth transition GARCH model, designed to accommodate Z-valued time series that display asymmetric, nonlinear and highly persistent volatility. The article outlines the maximum likelihood estimation procedure and establishes its consistency and asymptotic normality of the estimated parameters. Three types of tests are studied, including sup-type linearity test, score-based goodness-of-fit test, and residual-based mi...