Journal of the American Statistical Association

最新文章

• New Tests for Equality of Several Covariance Functions for Functional Data AI翻译
  作者：Guo, Jia; Zhou, Bu; Zhang, Jin-Ting
  作者单位：Zhejiang University of Technology; University of Melbourne; University of Melbourne; Zhejiang Gongshang University; National University of Singapore
  摘要：In this article, we propose two new tests for the equality of the covariance functions of several functional populations, namely, a quasi-GPF test and a quasi-F-max test whose test statistics are obtained via globalizing a pointwise quasi-F-test statistic with integration and taking its supremum over some time interval of interest, respectively. Unlike several existing tests, they are scale-invariant in the sense that their test statistics will not change if we multiply each of the observed fu...
• On the Use of the Lasso for Instrumental Variables Estimation with Some Invalid Instruments AI翻译
  作者：Windmeijer, Frank; Farbmacher, Helmut; Davies, Neil; Smith, George Davey
  作者单位：University of Bristol; Max Planck Society; University of Bristol
  摘要：We investigate the behavior of the Lasso for selecting invalid instruments in linear instrumental variables models for estimating causal effects of exposures on outcomes, as proposed recently by Kang et al. Invalid instruments are such that they fail the exclusion restriction and enter the model as explanatory variables. We show that for this setup, the Lasso may not consistently select the invalid instruments if these are relatively strong. We propose a median estimator that is consistent whe...
• Parameter Estimation and Variable Selection for Big Systems of Linear Ordinary Differential Equations: A Matrix-Based Approach AI翻译
  作者：Wu, Leqin; Qiu, Xing; Yuan, Ya-xiang; Wu, Hulin
  作者单位：Jinan University; University of Rochester; Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS; University of Texas System; University of Texas Health Science Center Houston
  摘要：Ordinary differential equations (ODEs) are widely used to model the dynamic behavior of a complex system. Parameter estimation and variable selection for a Big System with linear ODEs are very challenging due to the need of nonlinear optimization in an ultra-high dimensional parameter space. In this article, we develop a parameter estimation and variable selection method based on the ideas of similarity transformation and separable least squares (SLS). Simulation studies demonstrate that the p...
• Minimum Mean Squared Error Estimation of the Radius of Gyration in Small-Angle X-Ray Scattering Experiments AI翻译
  作者：Alsaker, Cody; Breidt, F. Jay; van der Woerd, Mark J.
  作者单位：Colorado State University System; Colorado State University Fort Collins; Colorado State University System; Colorado State University Fort Collins
  摘要：Small-angle X-ray scattering (SAXS) is a technique that yields low-resolution structural information of biological macromolecules by exposing a large ensemble of molecules in solution to a powerful X-ray beam. The beam interacts with the molecules and the intensity of the scattered beam is recorded on a detector plate. The radius of gyration for a molecule, which is a measure of the spread of its mass, can be estimated from the lowest scattering angles of SAXS data. This estimation method requ...
• The Blessings of Multiple Causes AI翻译
  作者：Wang, Yixin; Blei, David M.
  作者单位：Columbia University; Columbia University
  摘要：Causal inference from observational data is a vital problem, but it comes with strong assumptions. Most methods assume that we observe all confounders, variables that affect both the causal variables and the outcome variables. This assumption is standard but it is also untestable. In this article, we develop the deconfounder, a way to do causal inference with weaker assumptions than the traditional methods require. The deconfounder is designed for problems of multiple causal inference: scienti...
• Selection-Corrected Statistical Inference for Region Detection With High-Throughput Assays AI翻译
  作者：Benjamini, Yuval; Taylor, Jonathan; Irizarry, Rafael A.
  作者单位：Hebrew University of Jerusalem; Stanford University; Harvard University; Harvard University Medical Affiliates; Dana-Farber Cancer Institute; Harvard University
  摘要：Scientists use high-dimensional measurement assays to detect and prioritize regions of strong signal in spatially organized domain. Examples include finding methylation-enriched genomic regions using microarrays, and active cortical areas using brain-imaging. The most common procedure for detecting potential regions is to group neighboring sites where the signal passed a threshold. However, one needs to account for the selection bias induced by this procedure to avoid diminishing effects when ...
• Semiparametric Regression Analysis of Multiple Right- and Interval-Censored Events AI翻译
  作者：Gao, Fei; Zeng, Donglin; Couper, David; Lin, D. Y.
  作者单位：University of North Carolina; University of North Carolina Chapel Hill
  摘要：Health sciences research often involves both right- and interval-censored events because the occurrence of a symptomatic disease can only be observed up to the end of follow-up, while the occurrence of an asymptomatic disease can only be detected through periodic examinations. We formulate the effects of potentially time-dependent covariates on the joint distribution of multiple right- and interval-censored events through semiparametric proportional hazards models with random effects that capt...
• Bootstrapping High-Frequency Jump Tests AI翻译
  作者：Dovonon, Prosper; Goncalves, Silvia; Hounyo, Ulrich; Meddahi, Nour
  作者单位：Concordia University - Canada; McGill University; State University of New York (SUNY) System; University at Albany, SUNY; CREATES; Universite de Toulouse; Universite Toulouse 1 Capitole; Toulouse School of Economics
  摘要：The main contribution of this article is to propose a bootstrap test for jumps based on functions of realized volatility and bipower variation. Bootstrap intraday returns are randomly generated from a mean zero Gaussian distribution with a variance given by a local measure of integrated volatility (which we denote by ). We first discuss a set of high-level conditions on such that any bootstrap test of this form has the correct asymptotic size and is alternative-consistent. We then provide a se...
• Variance Change Point Detection Under a Smoothly-Changing Mean Trend with Application to Liver Procurement AI翻译
  作者：Gao, Zhenguo; Shang, Zuofeng; Du, Pang; Robertson, John L.
  作者单位：Virginia Polytechnic Institute & State University; Indiana University System; Indiana University Indianapolis; Virginia Polytechnic Institute & State University
  摘要：Literature on change point analysis mostly requires a sudden change in the data distribution, either in a few parameters or the distribution as a whole. We are interested in the scenario, where the variance of data may make a significant jump while the mean changes in a smooth fashion. The motivation is a liver procurement experiment monitoring organ surface temperature. Blindly applying the existing methods to the example can yield erroneous change point estimates since the smoothly changing ...
• Bayesian Model Comparison with the Hyvarinen Score: Computation and Consistency AI翻译
  作者：Shao, Stephane; Jacob, Pierre E.; Ding, Jie; Tarokh, Vahid
  作者单位：Harvard University; University of Minnesota System; University of Minnesota Twin Cities; Duke University
  摘要：The Bayes factor is a widely used criterion in model comparison and its logarithm is a difference of out-of-sample predictive scores under the logarithmic scoring rule. However, when some of the candidate models involve vague priors on their parameters, the log-Bayes factor features an arbitrary additive constant that hinders its interpretation. As an alternative, we consider model comparison using the Hyvarinen score. We propose a method to consistently estimate this score for parametric mode...