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作者：Lock, Eric F.; Dunson, David B.
作者单位：University of Minnesota System; University of Minnesota Twin Cities; Duke University
摘要：This article concerns testing for equality of distribution between groups. We focus on screening variables with shared distributional features such as common support, modes and patterns of skewness. We propose a Bayesian testing method using kernel mixtures, which improves performance by borrowing information across the different variables and groups through shared kernels and a common probability of group differences. The inclusion of shared kernels in a finite mixture, with Dirichlet priors ...
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作者：Dobriban, Edgar; Fortney, Kristen; Kim, Stuart K.; Owen, Art B.
作者单位：Stanford University; Stanford University
摘要：We develop a new method for large-scale frequentist multiple testing with Bayesian prior information. We find optimal p-value weights that maximize the average power of the weighted Bonferroni method. Due to the nonconvexity of the optimization problem, previous methods that account for uncertain prior information are suitable for only a small number of tests. For a Gaussian prior on the effect sizes, we give an efficient algorithm that is guaranteed to find the optimal weights nearly exactly....
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作者：Peyhardi, J.; Trottier, C.; Guedon, Y.
作者单位：Universite de Montpellier; Universite de Montpellier; Universite Paul-Valery
摘要：Many regression models for categorical responses have been introduced, motivated by different paradigms, but it is difficult to compare them because of their different specifications. In this paper we propose a unified specification of regression models for categorical responses, based on a decomposition of the link function into an inverse continuous cumulative distribution function and a ratio of probabilities. This allows us to define a new family of reference models for nominal responses, ...
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作者：Dette, H.; Kettelhake, K.; Bretz, F.
作者单位：Ruhr University Bochum; Novartis
摘要：Optimal design of dose-finding studies with an active control has only been considered in the literature for regression models with normally distributed errors and known variances, where the focus is on estimating the smallest dose that achieves the same treatment effect as the active control. This paper discusses such dose-finding studies from a broader perspective. We consider a general class of optimality criteria and models arising from an exponential family. Optimal designs are constructe...
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作者：Matsuda, Takeru; Komaki, Fumiyasu
作者单位：University of Tokyo
摘要：We develop singular value shrinkage priors for the mean matrix parameters in the matrix-variate normal model with known covariance matrices. Our priors are superharmonic and put more weight on matrices with smaller singular values. They are a natural generalization of the Stein prior. Bayes estimators and Bayesian predictive densities based on our priors are minimax and dominate those based on the uniform prior in finite samples. In particular, our priors work well when the true value of the p...
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作者：Singh, Rakhi; Chai, Feng-Shun; Das, Ashish
作者单位：Indian Institute of Technology System (IIT System); Indian Institute of Technology (IIT) - Bombay; Academia Sinica - Taiwan; Indian Institute of Technology System (IIT System); Indian Institute of Technology (IIT) - Bombay
摘要：For two-level choice experiments, we obtain a simple form of the information matrix of a choice design for estimating the main effects, and provide D- and MS-optimal paired choice designs with distinct choice sets under the main effects model for any number of choice sets. It is shown that the optimal designs under the main effects model are also optimal under the broader main effects model. We find that optimal choice designs with a choice set size two often outperform their counterparts with...
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作者：Thibaud, Emeric; Opitz, Thomas
作者单位：Colorado State University System; Colorado State University Fort Collins; INRAE
摘要：Recent advances in extreme value theory have established l-Pareto processes as the natural limits for extreme events defined in terms of exceedances of a risk functional. In this paper we provide methods for the practical modelling of data based on a tractable yet flexible dependence model. We introduce the class of elliptical l-Pareto processes, which arise as the limits of threshold exceedances of certain elliptical processes characterized by a correlation function and a shape parameter. An ...
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作者：Zhou, Yongdao; Xu, Hongquan
作者单位：Sichuan University; University of California System; University of California Los Angeles
摘要：We study space-filling properties of good lattice point sets and obtain some general theoretical results. We show that linear level permutation does not decrease the minimum distance for good lattice point sets, and we identify several classes of such sets with large minimum distance. Based on good lattice point sets, some maximin distance designs are also constructed.
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作者：Zhu, Hongtu; Ibrahim, Joseph G.; Chen, Ming-Hui
作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of Connecticut
摘要：We investigate diagnostic measures for assessing the influence of observations and model misspecification on the Cox regression model when there are missing covariate data. Our diagnostics include case-deletion measures, conditional martingale residuals, and score residuals. The Q-distance is introduced to examine the effects of deleting individual observations on the estimates of finite- and infinite-dimensional parameters. Conditional martingale residuals are used to construct goodness-of-fi...
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作者：Camponovo, L.
作者单位：University of St Gallen
摘要：We study the validity of the pairs bootstrap for lasso estimators in linear regression models with random covariates and heteroscedastic error terms. We show that the naive pairs bootstrap does not provide a valid method for approximating the distribution of the lasso estimator. To overcome this deficiency, we introduce a modified pairs bootstrap procedure and prove its consistency. Finally, we consider the adaptive lasso and show that the modified pairs bootstrap consistently estimates the di...
