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作者：Bissiri, P. G.; Holmes, C. C.; Walker, S. G.
作者单位：University of Milano-Bicocca; University of Oxford; University of Texas System; University of Texas Austin
摘要：We propose a framework for general Bayesian inference. We argue that a valid update of a prior belief distribution to a posterior can be made for parameters which are connected to observations through a loss function rather than the traditional likelihood function, which is recovered as a special case. Modern application areas make it increasingly challenging for Bayesians to attempt to model the true data-generating mechanism. For instance, when the object of interest is low dimensional, such...
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作者：Zhu, Ke
作者单位：Chinese Academy of Sciences
摘要：The paper uses a random-weighting (RW) method to bootstrap the critical values for the Ljung-Box or Monti portmanteau tests and weighted Ljung-Box or Monti portmanteau tests in weak auto-regressive moving average models. Unlike the existing methods, no user-chosen parameter is needed to implement the RW method. As an application, these four tests are used to check the model adequacy in power generalized auto-regressive conditional heteroscedasticity models. Simulation evidence indicates that t...
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作者：Patra, Rohit Kumar; Sen, Bodhisattva
作者单位：Columbia University
摘要：We consider a two-component mixture model with one known component. We develop methods for estimating the mixing proportion and the unknown distribution non-parametrically, given independent and identically distributed data from the mixture model, using ideas from shape-restricted function estimation. We establish the consistency of our estimators. We find the rate of convergence and asymptotic limit of the estimator for the mixing proportion. Completely automated distribution-free honest fini...
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作者：Ding, Peng; Feller, Avi; Miratrix, Luke
作者单位：Harvard University
摘要：Applied researchers are increasingly interested in whether and how treatment effects vary in randomized evaluations, especially variation that is not explained by observed covariates. We propose a model-free approach for testing for the presence of such unexplained variation. To use this randomization-based approach, we must address the fact that the average treatment effect, which is generally the object of interest in randomized experiments, actually acts as a nuisance parameter in this sett...
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作者：Fryzlewicz, Piotr; Van Keilegom, Ingrid
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作者：Daouia, Abdelaati; Noh, Hohsuk; Park, Byeong U.
作者单位：Universite de Toulouse; Universite Catholique Louvain; Sookmyung Women's University; Seoul National University (SNU)
摘要：Estimation of support frontiers and boundaries often involves monotone and/or concave edge data smoothing. This estimation problem arises in various unrelated contexts, such as optimal cost and production assessments in econometrics and master curve prediction in the reliability programmes of nuclear reactors. Very few constrained estimators of the support boundary of a bivariate distribution have been introduced in the literature. They are based on simple envelopment techniques which often su...
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作者：Berger, Y. G.; Torres, O. De La Riva
作者单位：University of Southampton; Instituto Nacional de Salud Publica
摘要：We define an empirical likelihood approach which gives consistent design-based confidence intervals which can be calculated without the need of variance estimates, designeffects, resampling, joint inclusion probabilities and linearization, even when the point estimator is not linear. It can be used to construct confidence intervals for a large class of sampling designs and estimators which are solutions of estimating equations. It can be used for means, regressions coefficients, quantiles, tot...
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作者：Qiu, Huitong; Han, Fang; Liu, Han; Caffo, Brian
作者单位：Johns Hopkins University; Princeton University
摘要：We consider the problem of jointly estimating multiple graphical models in high dimensions. We assume that the data are collected from n subjects, each of which consists of T possibly dependent observations. The graphical models of subjects vary, but are assumed to change smoothly corresponding to a measure of closeness between subjects. We propose a kernel-based method for jointly estimating all graphical models. Theoretically, under a double asymptotic framework, where both (T,n) and the dim...
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作者：Bickel, Peter J.; Sarkar, Purnamrita
作者单位：University of California System; University of California Berkeley; University of Texas System; University of Texas Austin
摘要：Community detection in networks is a key exploratory tool with applications in a diverse set of areas, ranging from finding communities in social and biological networks to identifying link farms in the World Wide Web. The problem of finding communities or clusters in a network has received much attention from statistics, physics and computer science. However, most clustering algorithms assume knowledge of the number of clusters k. We propose to determine k automatically in a graph generated f...
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作者：Polson, Nicholas G.; Scott, James G.
作者单位：University of Chicago; University of Texas System; University of Texas Austin
摘要：We develop a connection between mixture and envelope representations of objective functions that arise frequently in statistics. We refer to this connection by using the term hierarchical duality'. Our results suggest an interesting and previously underexploited relationship between marginalization and profiling, or equivalently between the Fenchel-Moreau theorem for convex functions and the Bernstein-Widder theorem for Laplace transforms. We give several different sets of conditions under whi...
