Journal of the American Statistical Association

最新文章

• Malware Family Discovery Using Reversible Jump MCMC Sampling of Regimes AI翻译
  作者：Bolton, Alexander D.; Heard, Nicholas A.
  作者单位：Imperial College London; University of Bristol
  摘要：Malware is computer software that has either been designed or modified with malicious intent. Hundreds of thousands of new malware threats appear on the internet each day. This is made possible through reuse of known exploits in computer systems that have not been fully eradicated; existing pieces of malware can be trivially modified and combined to create new malware, which is unknown to anti-virus programs. Finding new software with similarities to known malware is therefore an important goa...
• Invariant Inference and Efficient Computation in the Static Factor Model AI翻译
  作者：Chan, Joshua; Leon-Gonzalez, Roberto; Strachan, Rodney W.
  作者单位：University of Technology Sydney; National Graduate Institute for Policy Studies; University of Queensland
  摘要：Factor models are used in a wide range of areas. Two issues with Bayesian versions of these models are a lack of invariance to ordering of and scaling of the variables and computational inefficiency. This article develops invariant and efficient Bayesian methods for estimating static factor models. This approach leads to inference that does not depend upon the ordering or scaling of the variables, and we provide arguments to explain this invariance. Beginning from identified parameters which a...
• A Tailored Multivariate Mixture Model for Detecting Proteins of Concordant Change Among Virulent Strains of Clostridium Perfringens AI翻译
  作者：Chen, Kun; Mishra, Neha; Smyth, Joan; Bar, Haim; Schifano, Elizabeth; Kuo, Lynn; Chen, Ming-Hui
  作者单位：University of Connecticut; University of Connecticut
  摘要：Necrotic enteritis (NE) is a serious disease of poultry caused by the bacterium C. perfringens. To identify proteins of C. perfringens that confer virulence with respect to NE, the protein secretions of four NE disease-producing strains and one baseline nondisease-producing strain of C. perfringens were examined. The problem then becomes a clustering task, for the identification of two extreme groups of proteins that were produced at either concordantly higher or concordantly lower levels acro...
• To Wait or Not to Wait: Two-Way Functional Hazards Model for Understanding Waiting in Call Centers AI翻译
  作者：Li, Gen; Huang, Jianhua Z.; Shen, Haipeng
  作者单位：Columbia University; Texas A&M University System; Texas A&M University College Station; University of Hong Kong
  摘要：Telephone call centers offer a convenient communication channel between businesses and their customers. Efficient management of call centers needs accurate modeling of customer waiting behavior, which contains important information about customer patience (how long a customer is willing to wait) and service quality (how long a customer needs to wait to get served). Hazard functions offer dynamic characterization of customer waiting behavior, and provide critical inputs for agent scheduling. Mo...
• Optimal Probability Weights for Inference With Constrained Precision AI翻译
  作者：Santacatterina, Michele; Bottai, Matteo
  作者单位：Karolinska Institutet
  摘要：Probability weights are used in many areas of research including complex survey designs, missing data analysis, and adjustment for confounding factors. They are useful analytic tools but can lead to statistical inefficiencies when they contain outlying values. This issue is frequently tackled by replacing large weights with smaller ones or by normalizing them through smoothing functions. While these approaches are practical, they are also prone to yield biased inferences. This article introduc...
• A Bayesian Approach for Estimating Dynamic Functional Network Connectivity in fMRI Data AI翻译
  作者：Warnick, Ryan; Guindani, Michele; Erhardt, Erik; Allen, Elena; Calhoun, Vince; Vannucci, Marina
  作者单位：Rice University; University of California System; University of California Irvine; University of New Mexico; University of New Mexico; University of New Mexico
  摘要：Dynamic functional connectivity, that is, the study of how interactions among brain regions change dynamically over the course of an fMRI experiment, has recently received wide interest in the neuroimaging literature. Current approaches for studying dynamic connectivity often rely on ad hoc approaches for inference, with the fMRI time courses segmented by a sequence of sliding windows. We propose a principled Bayesian approach to dynamic functional connectivity, which is based on the estimatio...
• Minimax Optimal Procedures for Locally Private Estimation Comment AI翻译
  作者：Zhang, Anderson Y.; Zhou, Harrison H.
  作者单位：Yale University
• Efficient Estimation of the Nonparametric Mean and Covariance Functions for Longitudinal and Sparse Functional Data AI翻译
  作者：Zhou, Ling; Lin, Huazhen; Liang, Hua
  作者单位：Southwestern University of Finance & Economics - China; Southwestern University of Finance & Economics - China; George Washington University
  摘要：We consider the estimation of mean and covariance functions for longitudinal and sparse functional data by using the full quasi-likelihood coupling a modification of the local kernel smoothing method. The proposed estimators are shown to be consistent, asymptotically normal, and semiparametrically efficient in terms of their linear functionals. Their superiority to the competitors is further illustrated numerically through simulation studies. The method is applied to analyze AIDS study and atm...
• Design-Based Maps for Finite Populations of Spatial Units AI翻译
  作者：Fattorini, L.; Marcheselli, M.; Pratelli, L.
  作者单位：University of Siena
  摘要：The estimation of the values of a survey variable in finite populations of spatial units is considered for making maps when samples of spatial units are selected by probabilistic sampling schemes. The single values are estimated by means of an inverse distance weighting predictor. The design-based asymptotic properties of the resulting maps, referred to as the design-based maps, are considered when the study area remains fixed and the sizes of the spatial units tend to zero. Conditions ensurin...
• Distribution-Free Predictive Inference for Regression AI翻译
  作者：Lei, Jing; G'Sell, Max; Rinaldo, Alessandro; Tibshirani, Ryan J.; Wasserman, Larry
  作者单位：Carnegie Mellon University
  摘要：We develop a general framework for distribution-free predictive inference in regression, using conformal inference. The proposed methodology allows for the construction of a prediction band for the response variable using any estimator of the regression function. The resulting prediction band preserves the consistency properties of the original estimator under standard assumptions, while guaranteeing finite-sample marginal coverage even when these assumptions do not hold. We analyze and compar...