2018

最新文章

• Detecting heteroscedasticity in non-parametric regression using weighted empirical processes AI翻译
  作者：Chown, Justin; Mueller, Ursula U.
  作者单位：Ruhr University Bochum; Texas A&M University System; Texas A&M University College Station
  摘要：Heteroscedastic errors can lead to inaccurate statistical conclusions if they are not properly handled. We introduce a test for heteroscedasticity for the non-parametric regression model with multiple covariates. It is based on a suitable residual-based empirical distribution function. The residuals are constructed by using local polynomial smoothing. Our test statistic involves a detection function' that can verify heteroscedasticity by exploiting just the independence-dependence structure be...
• Maximin projection learning for optimal treatment decision with heterogeneous individualized treatment effects AI翻译
  作者：Shi, Chengchun; Song, Rui; Lu, Wenbin; Fu, Bo
  作者单位：North Carolina State University; Fudan University
  摘要：A salient feature of data from clinical trials and medical studies is inhomogeneity. Patients not only differ in baseline characteristics, but also in the way that they respond to treatment. Optimal individualized treatment regimes are developed to select effective treatments based on patient's heterogeneity. However, the optimal treatment regime might also vary for patients across different subgroups. We mainly consider patients' heterogeneity caused by groupwise individualized treatment effe...
• Bounded, efficient and multiply robust estimation of average treatment effects using instrumental variables AI翻译
  作者：Wang, Linbo; Tchetgen, Eric Tchetgen
  作者单位：Harvard University; Harvard T.H. Chan School of Public Health
  摘要：Instrumental variables are widely used for estimating causal effects in the presence of unmeasured confounding. Under the standard instrumental variable model, however, the average treatment effect is only partially identifiable. To address this, we propose novel assumptions that enable identification of the average treatment effect. Our identification assumptions are clearly separated from model assumptions that are needed for estimation, so researchers are not required to commit to a specifi...
• A geometric approach to confidence regions and bands for functional parameters AI翻译
  作者：Choi, Hyunphil; Reimherr, Matthew
  作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
  摘要：Functional data analysis is now a well-established discipline of statistics, with its core concepts and perspectives in place. Despite this, there are still fundamental statistical questions which have received relatively little attention. One of these is the systematic construction of confidence regions for functional parameters. This work is concerned with developing, understanding and visualizing such regions. We provide a general strategy for constructing confidence regions in a real separ...
• Confidence intervals for causal effects with invalid instruments by using two-stage hard thresholding with voting AI翻译
  作者：Guo, Zijian; Kang, Hyunseung; Cai, T. Tony; Small, Dylan S.
  作者单位：Rutgers University System; Rutgers University New Brunswick; University of Wisconsin System; University of Wisconsin Madison; University of Pennsylvania
  摘要：A major challenge in instrumental variable (IV) analysis is to find instruments that are valid, or have no direct effect on the outcome and are ignorable. Typically one is unsure whether all of the putative IVs are in fact valid. We propose a general inference procedure in the presence of invalid IVs, called two-stage hard thresholding with voting. The procedure uses two hard thresholding steps to select strong instruments and to generate candidate sets of valid IVs. Voting takes the candidate...
• Asymptotic properties and information criteria for misspecified generalized linear mixed models AI翻译
  作者：Yu, Dalei; Zhang, Xinyu; Yau, Kelvin K. W.
  作者单位：Yunnan University of Finance & Economics; Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS; City University of Hong Kong
  摘要：The problem of misspecification poses challenges in model selection. The paper studies the asymptotic properties of estimators for generalized linear mixed models with misspecification under the framework of conditional Kullback-Leibler divergence. A conditional generalized information criterion is introduced, and a model selection procedure is proposed by minimizing the criterion. We prove that the model selection procedure proposed is asymptotically loss efficient when all the candidate mode...
• Sparse generalized eigenvalue problem: optimal statistical rates via truncated Rayleigh flow AI翻译
  作者：Tan, Kean Ming; Wang, Zhaoran; Liu, Han; Zhang, Tong
  作者单位：University of Minnesota System; University of Minnesota Twin Cities; Northwestern University
  摘要：The sparse generalized eigenvalue problem (GEP) plays a pivotal role in a large family of high dimensional statistical models, including sparse Fisher's discriminant analysis, canonical correlation analysis and sufficient dimension reduction. The sparse GEP involves solving a non-convex optimization problem. Most existing methods and theory in the context of specific statistical models that are special cases of the sparse GEP require restrictive structural assumptions on the input matrices. We...