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作者：Li, Housen; Munk, Axel; Sieling, Hannes; Walther, Guenther
作者单位：University of Gottingen; Stanford University
摘要：The histogram is widely used as a simple, exploratory way of displaying data, but it is usually not clear how to choose the number and size of the bins. We construct a confidence set of distribution functions that optimally deal with the two main tasks of the histogram: estimating probabilities and detecting features such as increases and modes in the distribution. We define the essential histogram as the histogram in the confidence set with the fewest bins. Thus the essential histogram is the...
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作者：Lee, Jarod Y. L.; Green, Peter J.; Ryan, Louise M.
作者单位：University of Technology Sydney
摘要：This article concerns a class of generalized linear mixed models for two-level grouped data, where the random effects are uniquely indexed by groups and are independent. We derive necessary and sufficient conditions for the marginal likelihood to be expressed in explicit form. These models are unified under the conjugate generalized linear mixed models framework, where conjugate refers to the fact that the marginal likelihood can be expressed in closed form, rather than implying inference via ...
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作者：Sen, Deborshee; Sachs, Matthias; Lu, Jianfeng; Dunson, David B.
作者单位：Duke University; Duke University
摘要：Classification with high-dimensional data is of widespread interest and often involves dealing with imbalanced data. Bayesian classification approaches are hampered by the fact that current Markov chain Monte Carlo algorithms for posterior computation become inefficient as the number of predictors or the number of subjects to classify gets large, because of the increasing computational time per step and worsening mixing rates. One strategy is to employ a gradient-based sampler to improve mixin...
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作者：Dobriban, E.
作者单位：University of Pennsylvania
摘要：Multiple hypothesis testing problems arise naturally in science. This note introduces a new fast closed testing method for multiple testing which controls the familywise error rate. Controlling the familywise error rate is state-of-the-art in many important application areas and is preferred over false discovery rate control for many reasons, including that it leads to stronger reproducibility. The closure principle rejects an individual hypothesis if all global nulls of subsets containing it ...
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作者：Jiang, Zhichao; Ding, Peng
作者单位：University of Massachusetts System; University of Massachusetts Amherst; University of California System; University of California Berkeley
摘要：Instrumental variable methods can identify causal effects even when the treatment and outcome are confounded. We study the problem of imperfect measurements of the binary instrumental variable, treatment and outcome. We first consider nondifferential measurement errors, that is, the mismeasured variable does not depend on other variables given its true value. We show that the measurement error of the instrumental variable does not bias the estimate, that the measurement error of the treatment ...
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作者：Lijoi, Antonio; Prunster, Igor; Rigon, Tommaso
作者单位：Bocconi University
摘要：Discrete nonparametric priors play a central role in a variety of Bayesian procedures, most notably when used to model latent features, such as in clustering, mixtures and curve fitting. They are effective and well-developed tools, though their infinite dimensionality is unsuited to some applications. If one restricts to a finite-dimensional simplex, very little is known beyond the traditional Dirichlet multinomial process, which is mainly motivated by conjugacy. This paper introduces an alter...
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作者：Simpson, E. S.; Wadsworth, J. L.; Tawn, J. A.
作者单位：Lancaster University
摘要：In multivariate extreme value analysis, the nature of the extremal dependence between variables should be considered when selecting appropriate statistical models. Interest often lies in determining which subsets of variables can take their largest values simultaneously while the others are of smaller order. Our approach to this problem exploits hidden regular variation properties on a collection of nonstandard cones, and provides a new set of indices that reveal aspects of the extremal depend...
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作者：Bellach, A.; Kosorok, M. R.; Gilbert, P. B.; Fine, J. P.
作者单位：University of Washington; University of Washington Seattle; University of North Carolina; University of North Carolina Chapel Hill; Fred Hutchinson Cancer Center
摘要：Left-truncation poses extra challenges for the analysis of complex time-to-event data. We propose a general semiparametric regression model for left-truncated and right-censored competing risks data that is based on a novel weighted conditional likelihood function. Targeting the subdistribution hazard, our parameter estimates are directly interpretable with regard to the cumulative incidence function. We compare different weights from recent literature and develop a heuristic interpretation fr...
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作者：Guo, F. Richard; Richardson, Thomas S.
作者单位：University of Washington; University of Washington Seattle
摘要：We consider testing marginal independence versus conditional independence in a trivariate Gaussian setting. The two models are nonnested, and their intersection is a union of two marginal independences. We consider two sequences of such models, one from each type of independence, that are closest to each other in the Kullback-Leibler sense as they approach the intersection. They become indistinguishable if the signal strength, as measured by the product of two correlation parameters, decreases...
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作者：Tyler, David E.; Yi, Mengxi
作者单位：Rutgers University System; Rutgers University New Brunswick; University of International Business & Economics
摘要：The properties of penalized sample covariance matrices depend on the choice of the penalty function. In this paper, we introduce a class of nonsmooth penalty functions for the sample covariance matrix and demonstrate how their use results in a grouping of the estimated eigenvalues. We refer to the proposed method as lassoing eigenvalues, or the elasso.
