2017

最新文章

• Optimal group testing designs for estimating prevalence with uncertain testing errors AI翻译
  作者：Huang, Shih-Hao; Huang, Mong-Na Lo; Shedden, Kerby; Wong, Weng Kee
  作者单位：National Sun Yat Sen University; Academia Sinica - Taiwan; University of Michigan System; University of Michigan; University of California System; University of California Los Angeles
  摘要：We construct optimal designs for group testing experiments where the goal is to estimate the prevalence of a trait by using a test with uncertain sensitivity and specificity. Using optimal design theory for approximate designs, we show that the most efficient design for simultaneously estimating the prevalence, sensitivity and specificity requires three different group sizes with equal frequencies. However, if estimating prevalence as accurately as possible is the only focus, the optimal strat...
• Estimation of the false discovery proportion with unknown dependence AI翻译
  作者：Fan, Jianqing; Han, Xu
  作者单位：Princeton University; Fudan University; Pennsylvania Commonwealth System of Higher Education (PCSHE); Temple University
  摘要：Large-scale multiple testing with correlated test statistics arises frequently in much scientific research. Incorporating correlation information in approximating the false discovery proportion (FDP) has attracted increasing attention in recent years. When the covariance matrix of test statistics is known, Fan and his colleagues provided an accurate approximation of the FDP under arbitrary dependence structure and some sparsity assumption. However, the covariance matrix is often unknown in man...
• Statistical clustering of temporal networks through a dynamic stochastic block model AI翻译
  作者：Matias, Catherine; Miele, Vincent
  作者单位：Centre National de la Recherche Scientifique (CNRS); Sorbonne Universite; Sorbonne Universite; Universite Paris Cite; Centre National de la Recherche Scientifique (CNRS); Universite Claude Bernard Lyon 1; VetAgro Sup
  摘要：Statistical node clustering in discrete time dynamic networks is an emerging field that raises many challenges. Here, we explore statistical properties and frequentist inference in a model that combines a stochastic block model for its static part with independent Markov chains for the evolution of the nodes groups through time. We model binary data as well as weighted dynamic random graphs ( with discrete or continuous edges values). Our approach, motivated by the importance of controlling fo...
• Linear and conic programming estimators in high dimensional errors-in-variables models AI翻译
  作者：Belloni, Alexandre; Rosenbaum, Mathieu; Tsybakov, Alexandre B.
  作者单位：Duke University; Sorbonne Universite; Institut Polytechnique de Paris; ENSAE Paris
  摘要：We consider the linear regression model with observation error in the design. In this setting, we allow the number of covariates to be much larger than the sample size. Several new estimation methods have been recently introduced for this model. Indeed, the standard lasso estimator or Dantzig selector turns out to become unreliable when only noisy regressors are available, which is quite common in practice. In this work, we propose and analyse a new estimator for the errors-in-variables model....
• Theoretical guarantees for approximate sampling from smooth and log-concave densities AI翻译
  作者：Dalalyan, Arnak S.
  摘要：Sampling from various kinds of distribution is an issue of paramount importance in statistics since it is often the key ingredient for constructing estimators, test procedures or confidence intervals. In many situations, exact sampling from a given distribution is impossible or computationally expensive and, therefore, one needs to resort to approximate sampling strategies. However, there is no well-developed theory providing meaningful non-asymptotic guarantees for the approximate sampling pr...
• Mediation analysis with time varying exposures and mediators AI翻译
  作者：VanderWeele, Tyler J.; Tchetgen, Eric J. Tchetgen
  作者单位：Harvard University; Harvard T.H. Chan School of Public Health
  摘要：We consider causal mediation analysis when exposures and mediators vary over time. We give non-parametric identification results, discuss parametric implementation and also provide a weighting approach to direct and indirect effects based on combining the results of two marginal structural models. We also discuss how our results give rise to a causal interpretation of the effect estimates produced from longitudinal structural equation models. When there are time varying confounders affected by...
• A minimum relative entropy based correlation model between the response and covariates AI翻译
  作者：Bhattacharya, Bhaskar; Al-Talib, Mohammad
  作者单位：Southern Illinois University System; Southern Illinois University; Yarmouk University
  摘要：A semiparametric model is presented utilizing dependence between a response and several covariates. We show that this model is optimum when the marginal distributions of the response and the covariates are known. This model extends the generalized linear model and the proportional likelihood ratio model when the marginal distributions are unknown. New interpretations of known models such as the logistic regression model, density ratio model and selection bias model are obtained in terms of dep...
• Heterogeneous change point inference AI翻译
  作者：Pein, Florian; Sieling, Hannes; Munk, Axel
  作者单位：University of Gottingen; Max Planck Society
  摘要：We propose, a heterogeneous simultaneous multiscale change point estimator called 'H-SMUCE' for the detection of multiple change points of the signal in a heterogeneous Gaussian regression model. A piecewise constant function is estimated by minimizing the number of change points over the acceptance region of a multiscale test which locally adapts to changes in the variance. The multiscale test is a combination of local likelihood ratio tests which are properly calibrated by scale-dependent cr...
• Efficient estimation of semiparametric transformation models for the cumulative incidence of competing risks AI翻译
  作者：Mao, Lu; Lin, D. Y.
  作者单位：University of North Carolina; University of North Carolina Chapel Hill
  摘要：The cumulative incidence is the probability of failure from the cause of interest over a certain time period in the presence of other risks. A semiparametric regression model proposed by Fine and Gray has become the method of choice for formulating the effects of covariates on the cumulative incidence. Its estimation, however, requires modelling of the censoring distribution and is not statistically efficient. We present a broad class of semiparametric transformation models which extends the F...
• Direct and indirect treatment effects-causal chains and mediation analysis with instrumental variables AI翻译
  作者：Froelich, Markus; Huber, Martin
  作者单位：University of Mannheim; University of Fribourg
  摘要：The paper discusses the non-parametric identification of causal direct and indirect effects of a binary treatment based on instrumental variables. We identify the indirect effect, which operates through a mediator (i.e. intermediate variable) that is situated on the causal path between the treatment and the outcome, as well as the unmediated direct effect of the treatment by using distinct instruments for the endogenous treatment and the endogenous mediator. We examine various settings to obta...