Journal of the American Statistical Association

最新文章

• Boosting with the L2 loss:: Regression and classification AI翻译
  作者：Bühlmann, P; Yu, B
  作者单位：Swiss Federal Institutes of Technology Domain; ETH Zurich; University of California System; University of California Berkeley
  摘要：This article investigates a computationally simple variant of boosting, L(2)Boost, which is constructed from a functional gradient descent algorithm with the L-2-loss function. Like other boosting algorithms, L(2)Boost uses many times in an iterative fashion a prechosen fitting method, called the learner. Based on the explicit expression of refitting of residuals of L(2)Boost, the case with (symmetric) linear learners is studied in detail in both regression and classification. In particular, w...
• Bayesian modeling of markers of day-specific fertility AI翻译
  作者：Dunson, DB; Colombo, B
  作者单位：National Institutes of Health (NIH) - USA; NIH National Institute of Environmental Health Sciences (NIEHS); University of Padua
  摘要：Cervical mucus hydration increases during the fertile interval before ovulation. Because sperm. can only penetrate mucus having a high water content, cervical secretions provide a reliable marker of the fertile days of the menstrual cycle. This article develops a Bayesian approach for modeling of daily observations of cervical mucus and applies the approach to assess heterogeneity among women and cycles from a given woman with respect to the increase in mucus hydration during the fertile inter...
• Discovery of conserved sequence patterns using a stochastic dictionary model AI翻译
  作者：Gupta, M; Liu, JS
  作者单位：Harvard University
  摘要：Detection of unknown patterns from a randomly generated sequence of observations is a problem arising in fields ranging from signal processing to computational biology. Here we focus on the discovery of short recurring patterns (called motifs) in DNA sequences that represent binding sites for certain proteins in the process of gene regulation. What makes this a difficult problem is that these patterns can vary stochastically. We describe a novel data augmentation strategy for detecting such pa...
• Censored regression quantiles AI翻译
  作者：Portnoy, S
  作者单位：University of Illinois System; University of Illinois Urbana-Champaign
  摘要：Using quantile regression to analyze survival times offers an valuable complement to traditional Cox proportional hazards modelling. Unfortunately, this approach has been hampered by the lack of a conditional quantile estimator for censored data that is directly analogous to the Kaplan-Meier estimator and applies under standard assumptions for censored regression models. Here a recursively reweighted estimator of the regression quantile process is developed as a direct generalization of the Ka...
• Semiparametric estimation of multivariate fractional cointegration AI翻译
  作者：Chen, WW; Hurvich, CM
  作者单位：Texas A&M University System; Texas A&M University College Station; New York University
  摘要：We consider the semiparametric estimation of fractional cointegration in a multivariate process of cointegrating rank r > 0. We estimate the cointegrating relationships by the eigenvectors corresponding to the r smallest eigenvalues of an averaged periodogram matrix of tapered, differenced observations. The number of frequencies m used in the periodogram average is held fixed as the sample size grows. We first show that the averaged periodogram matrix converges in distribution to a singular ma...
• Likelihood-based inference in some continuous exponential families with unknown threshold parameters AI翻译
  作者：Dubinin, TM; Vardeman, SB
  作者单位：Iowa State University; Iowa State University
  摘要：We study likelihood-based inference in some continuous exponential families with unknown threshold parameters. The introduction of threshold parameters necessitates modification of the standard asymptotic arguments, and some possibly unexpected limiting distributions result.
• Finding the number of clusters in a dataset: An information-theoretic approach AI翻译
  作者：Sugar, CA; James, GM
  作者单位：University of Southern California
  摘要：One of the most difficult problems in cluster analysis is identifying the number of groups in a dataset. Most previously suggested approaches to this problem are either somewhat ad hoc or require parametric assumptions and complicated calculations. In. this article we develop a simple, yet powerful nonparametric method for choosing the number of clusters based on distortion, a quantity that measures the average distance, per dimension, between each observation and its closest cluster center. O...
• Inference and interpretability considerations in frequentist model averaging and selection - Discussion AI翻译
  作者：Cook, RD; Li, LX
  作者单位：University of Minnesota System; University of Minnesota Twin Cities; University of California System; University of California Davis
• Cox regression with accurate covariates unascertainable: A nonparametric-correction approach (vol 95, pg 1209, 2000) AI翻译
  作者：Huang, Y; Wang, CY
• The intrinsic distribution and selection bias of long-period cometary orbits AI翻译
  作者：Jupp, PE; Kim, PT; Koo, JY; Wiegert, P
  作者单位：University of St Andrews; University of Guelph; Inha University; Queens University - Canada
  摘要：A question that arises in the study of cometary orbits is whether or not the directed normals to the orbits are uniformly distributed on the celestial sphere. Previous studies by statisticians have not taken selection effects into account and have tended to reject uniformity. Here a plausible selection mechanism is proposed that gives rise to a one-parameter family of distributions on the sphere. Data on long-period comets are analyzed using this one-parameter family. A nonzero selection effec...