Journal of the American Statistical Association

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• Heteroscedasticity and Autocorrelation Robust Structural Change Detection AI翻译
  作者：Zhou, Zhou
  作者单位：University of Toronto
  摘要：The assumption of (weak) stationarity is crucial for the validity of most of the conventional tests of structure change in time series. Under complicated nonstationary temporal dynamics, we argue that traditional testing procedures result in mixed structural change signals of the first and second order and hence could lead to biased testing results. The article proposes a simple and unified bootstrap testing procedure that provides consistent testing results under general forms of smooth and a...
• Modeling and Forecasting Daily Electricity Load Curves: A Hybrid Approach AI翻译
  作者：Cho, Haeran; Goude, Yannig; Brossat, Xavier; Yao, Qiwei
  作者单位：University of London; London School Economics & Political Science; Electricite de France (EDF); Peking University
  摘要：We propose a hybrid approach for the modeling and the short-term forecasting of electricity loads. Two building blocks of our approach are (1) modeling the overall trend and seasonality by fitting a generalized additive model to the weekly averages of the load and (2) modeling the dependence structure across consecutive daily loads via curve linear regression. For the latter, a new methodology is proposed for linear regression with both curve response and curve regressors. The key idea behind ...
• Landmark Prediction of Long-Term Survival Incorporating Short-Term Event Time Information AI翻译
  作者：Parast, Layla; Cheng, Su-Chun; Cai, Tianxi
  作者单位：RAND Corporation; Harvard University; Harvard University Medical Affiliates; Dana-Farber Cancer Institute; Harvard University; Harvard T.H. Chan School of Public Health
  摘要：In recent years, a wide range of markers have become available as potential tools to predict risk or progression of disease. In addition to such biological and genetic markers, short-term outcome information may be useful in predicting long-term disease outcomes. When such information is available, it would be desirable to combine this along with predictive markers to improve the prediction of long-term survival. Most existing methods for incorporating censored short-term event information in ...
• A Class of Discrete Transformation Survival Models With Application to Default Probability Prediction AI翻译
  作者：Ding, A. Adam; Tian, Shaonan; Yu, Yan; Guo, Hui
  作者单位：Northeastern University; University System of Ohio; University of Cincinnati
  摘要：Corporate bankruptcy prediction plays a central role in academic finance research, business practice, and government regulation. Consequently, accurate default probability prediction is extremely important. We propose to apply a discrete transformation family of survival models to corporate default risk predictions. A class of Box-Cox transformations and logarithmic transformations is naturally adopted. The proposed transformation model family is shown to include the popular Shumway model and ...
• Application of Branching Models in the Study of Invasive Species AI翻译
  作者：Balderama, Earvin; Schoenberg, Frederic Paik; Murray, Erin; Rundel, Philip W.
  作者单位：University of California System; University of California Los Angeles; University of California System; University of California Los Angeles
  摘要：Earthquake occurrences are often described using a class of branching models called epidemic-type aftershock sequence (ETAS) models. The name derives from the fact that the model allows earthquakes to cause aftershocks, and then those aftershocks may induce subsequent aftershocks, and so on. Despite their value in seismology, such models have not previously been used in studying the incidence of invasive plant and animal species. Here, we apply ETAS models to study the spread of an invasive sp...
• Estimating Regression Parameters in an Extended Proportional Odds Model AI翻译
  作者：Chen, Ying Qing; Hu, Nan; Cheng, Su-Chun; Musoke, Philippa; Zhao, Lue Ping
  作者单位：Utah System of Higher Education; University of Utah; Harvard University; Harvard University Medical Affiliates; Dana-Farber Cancer Institute; Makerere University
  摘要：The proportional odds model may serve as a useful alternative to the Cox proportional hazards model to study association between covariates and their survival functions in medical studies. In this article, we study an extended proportional odds model that incorporates the so-called external time-varying covariates. In the extended model, regression parameters have a direct interpretation of comparing survival functions, without specifying the baseline survival odds function. Semiparametric and...
• Quantile Regression for Analyzing Heterogeneity in Ultra-High Dimension AI翻译
  作者：Wang, Lan; Wu, Yichao; Li, Runze
  作者单位：University of Minnesota System; University of Minnesota Twin Cities; North Carolina State University; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
  摘要：Ultra-high dimensional data often display heterogeneity due to either heteroscedastic variance or other forms of non-location-scale covariate effects. To accommodate heterogeneity, we advocate a more general interpretation of sparsity, which assumes that only a small number of covariates influence the conditional distribution of the response variable, given all candidate covariates; however, the sets of relevant covariates may differ when we consider different segments of the conditional distr...
• Objective Priors for Discrete Parameter Spaces AI翻译
  作者：Berger, James O.; Bernardo, Jose M.; Sun, Dongchu
  作者单位：Duke University; University of Valencia; East China Normal University; University of Missouri System; University of Missouri Columbia
  摘要：This article considers the development of objective prior distributions for discrete parameter spaces. Formal approaches to such development such as the reference prior approach-often result in a constant prior for a discrete parameter, which is questionable for problems that exhibit certain types of structure. To take advantage of structure, this article proposes embedding the original problem in a continuous problem that preserves the structure, and then using standard reference prior theory...
• Inference With Interference Between Units in an fMRI Experiment of Motor Inhibition AI翻译
  作者：Luo, Xi; Small, Dylan S.; Li, Chiang-Shan R.; Rosenbaum, Paul R.
  作者单位：Brown University; Brown University; University of Pennsylvania; Yale University
  摘要：An experimental unit is an opportunity to randomly apply or withhold a treatment. There is interference between units if the application of the treatment to one unit may also affect other units. In cognitive neuroscience, a common form of experiment presents a sequence of stimuli or requests for cognitive activity at random to each experimental subject and measures biological aspects of brain activity that follow these requests. Each subject is then many experimental units, and interference be...
• Modeling Nonstationary Processes Through Dimension Expansion AI翻译
  作者：Bornn, Luke; Shaddick, Gavin; Zidek, James V.
  作者单位：University of British Columbia; University of Bath
  摘要：In this article, we propose a novel approach to modeling nonstationary spatial fields. The proposed method works by expanding the geographic plane over which these processes evolve into higher-dimensional spaces, transforming and clarifying complex patterns in the physical plane. By combining aspects of multidimensional scaling, group lasso, and latent variable models, a dimensionally sparse projection is found in which the originally nonstationary field exhibits stationarity. Following a comp...