523期

最新文章

• Identifying Latent Structures in Restricted Latent Class Models AI翻译
  作者：Xu, Gongjun; Shang, Zhuoran
  作者单位：University of Michigan System; University of Michigan; University of Minnesota System; University of Minnesota Twin Cities
  摘要：This article focuses on a family of restricted latent structure models with wide applications in psychological and educational assessment, where the model parameters are restricted via a latent structure matrix to reflect prespecified assumptions on the latent attributes. Such a latent matrix is often provided by experts and assumed to be correct upon construction, yet it may be subjective and misspecified. Recognizing this problem, researchers have been developing methods to estimate the matr...
• On the Use of Reproducing Kernel Hilbert Spaces in Functional Classification AI翻译
  作者：Berrendero, Jose R.; Cuevas, Antonio; Torrecilla, Jose L.
  作者单位：Autonomous University of Madrid; Universidad Carlos III de Madrid
  摘要：The Hajek-Feldman dichotomy establishes that two Gaussian measures are either mutually absolutely continuous with respect to each other (and hence there is a Radon-Nikodym density for each measure with respect to the other one) or mutually singular. Unlike the case of finite-dimensional Gaussian measures, there are nontrivial examples of both situations when dealing with Gaussian stochastic processes. This article provides: (a) Explicit expressions for the optimal (Bayes) rule and the minimal ...
• Assessing Time-Varying Causal Effect Moderation in Mobile Health AI翻译
  作者：Boruvka, Audrey; Almirall, Daniel; Witkiewitz, Katie; Murphy, Susan A.
  作者单位：University of Michigan System; University of Michigan; University of Michigan System; University of Michigan; University of New Mexico
  摘要：In mobile health interventions aimed at behavior change and maintenance, treatments are provided in real time to manage current or impending high-risk situations or promote healthy behaviors in near real time. Currently there is great scientific interest in developing data analysis approaches to guide the development of mobile interventions. In particular data from mobile health studies might be used to examine effect moderatorsindividual characteristics, time-varying context, or past treatmen...
• Functional Feature Construction for Individualized Treatment Regimes AI翻译
  作者：Laber, Eric B.; Staicu, Ana-Maria
  作者单位：North Carolina State University
  摘要：Evidence-based personalized medicine formalizes treatment selection as an individualized treatment regime that maps up-to-date patient information into the space of possible treatments. Available patient information may include static features such race, gender, family history, genetic and genomic information, as well as longitudinal information including the emergence of comorbidities, waxing and waning of symptoms, side-effect burden, and adherence. Dynamic information measured at multiple t...
• Confidence Regions for Spatial Excursion Sets From Repeated Random Field Observations, With an Application to Climate AI翻译
  作者：Sommerfeld, Max; Sain, Stephan; Schwartzman, Armin
  作者单位：University of Gottingen; University of California System; University of California San Diego
  摘要：The goal of this article is to give confidence regions for the excursion set of a spatial function above a given threshold from repeated noisy observations on a fine grid of fixed locations. Given an asymptotically Gaussian estimator of the target function, a pair of data-dependent nested excursion sets are constructed that are sub- and super-sets of the true excursion set, respectively, with a desired confidence. Asymptotic coverage probabilities are determined via a multiplier bootstrap meth...
• On the Long-Run Volatility of Stocks AI翻译
  作者：Carvalho, Carlos M.; Lopes, Hedibert F.; McCulloch, Robert E.
  作者单位：University of Texas System; University of Texas Austin; Insper; University of Chicago; Arizona State University; Arizona State University-Tempe
  摘要：In this article, we investigate whether or not the volatility per period of stocks is lower over longer horizons. Taking the perspective of an investor, we evaluate the predictive variance of k-period returns under different model and prior specifications. We adopt the state-space framework of Pastor and Stambaugh to model the dynamics of expected returns and evaluate the effects of prior elicitation in the resulting volatility estimates. Part of the developments includes an extension that inc...
• Inference in Linear Regression Models with Many Covariates and Heteroscedasticity AI翻译
  作者：Cattaneo, Matias D.; Jansson, Michael; Newey, Whitney K.
  作者单位：University of Michigan System; University of Michigan; University of Michigan System; University of Michigan; University of California System; University of California Berkeley; Aarhus University; CREATES; Massachusetts Institute of Technology (MIT)
  摘要：The linear regression model is widely used in empirical work in economics, statistics, and many other disciplines. Researchers often include many covariates in their linear model specification in an attempt to control for confounders. We give inference methods that allow for many covariates and heteroscedasticity. Our results are obtained using high-dimensional approximations, where the number of included covariates is allowed to grow as fast as the sample size. We find that all of the usual v...
• Edge Exchangeable Models for Interaction Networks AI翻译
  作者：Crane, Harry; Dempsey, Walter
  作者单位：Rutgers University System; Rutgers University New Brunswick; University of Michigan System; University of Michigan
  摘要：Many modern network datasets arise from processes of interactions in a population, such as phone calls, email exchanges, co-authorships, and professional collaborations. In such interaction networks, the edges comprise the fundamental statistical units, making a framework for edge-labeled networks more appropriate for statistical analysis. In this context, we initiate the study of edge exchangeable network models and explore its basic statistical properties. Several theoretical and practical f...
• Quasi-Likelihood Estimation of a Censored Autoregressive Model With Exogenous Variables AI翻译
  作者：Wang, Chao; Chan, Kung-Sik
  作者单位：University of Iowa
  摘要：Maximum likelihood estimation of a censored autoregressive model with exogenous variables (CARX) requires computing the conditional likelihood of blocks of data of variable dimensions. As the random block dimension generally increases with the censoring rate, maximum likelihood estimation becomes quickly numerically intractable with increasing censoring. We introduce a new estimation approach using the complete-incomplete data framework with the complete data comprising the observations were t...
• Maximum Rank Reproducibility: A Nonparametric Approach to Assessing Reproducibility in Replicate Experiments AI翻译
  作者：Philtron, Daisy; Lyu, Yafei; Li, Qunhua; Ghosh, Debashis
  作者单位：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; Colorado School of Public Health; University of Colorado System; University of Colorado Anschutz Medical Campus
  摘要：The identification of reproducible signals from the results of replicate high-throughput experiments is an important part of modern biological research. Often little is known about the dependence structure and the marginal distribution of the data, motivating the development of a nonparametric approach to assess reproducibility. The procedure, which we call the maximum rank reproducibility (MaRR) procedure, uses a maximum rank statistic to parse reproducible signals from noise without making a...