-
作者：Molstad, Aaron J.; Rothman, Adam J.
作者单位：University of Minnesota System; University of Minnesota Twin Cities
摘要：We propose a class of estimators of the multivariate response linear regression coefficient matrix that exploits the assumption that the response and predictors have a joint multivariate normal distribution. This allows us to indirectly estimate the regression coefficient matrix through shrinkage estimation of the parameters of the inverse regression, or the conditional distribution of the predictors given the responses. We establish a convergence rate bound for estimators in our class and we ...
-
作者：Dombry, Clement; Engelke, Sebastian; Oesting, Marco
作者单位：Universite Marie et Louis Pasteur; Centre National de la Recherche Scientifique (CNRS); Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne; Universitat Siegen
摘要：Max-stable processes play an important role as models for spatial extreme events. Their complex structure as the pointwise maximum over an infinite number of random functions makes their simulation difficult. Algorithms based on finite approximations are often inexact and computationally inefficient. We present a new algorithm for exact simulation of a max-stable process at a finite number of locations. It relies on the idea of simulating only the extremal functions, that is, those functions i...
-
作者：Zhou, Yan; Song, Peter X. -K.
作者单位：University of Michigan System; University of Michigan
摘要：This paper concerns regression methodology for assessing relationships between multi-dimensional response variables and covariates that are correlated within a network. To address analytical challenges associated with the integration of network topology into the regression analysis, we propose a hybrid quadratic inference method that uses both prior and data-driven correlations among network nodes. A Godambe information-based tuning strategy is developed to allocate weights between the prior a...
-
作者：Kunihama, Tsuyoshi; Dunson, David B.
作者单位：University of Washington; University of Washington Seattle; Duke University
摘要：In many application areas, a primary focus is on assessing evidence in the data refuting the assumption of independence of Y and X conditionally on Z, with Y response variables, X predictors of interest, and Z covariates. Ideally, one would have methods available that avoid parametric assumptions, allow Y, X, Z to be random variables on arbitrary spaces with arbitrary dimension, and accommodate rapid consideration of different candidate predictors. As a formal decision-theoretic approach has c...
-
作者：Bhattacharya, Anirban; Chakraborty, Antik; Mallick, Bani K.
作者单位：Texas A&M University System; Texas A&M University College Station
摘要：We propose an efficient way to sample from a class of structured multivariate Gaussian distributions. The proposed algorithm only requires matrix multiplications and linear system solutions. Its computational complexity grows linearly with the dimension, unlike existing algorithms that rely on Cholesky factorizations with cubic complexity. The algorithm is broadly applicable in settings where Gaussian scale mixture priors are used on high-dimensional parameters. Its effectiveness is illustrate...
-
作者：Cressie, Noel; Zammit-Mangion, Andrew
作者单位：University of Wollongong
摘要：Multivariate geostatistics is based on modelling all covariances between all possible combinations of two or more variables at any sets of locations in a continuously indexed domain. Multivariate spatial covariance models need to be built with care, since any covariance matrix that is derived from such a model must be nonnegative-definite. In this article, we develop a conditional approach for spatial-model construction whose validity conditions are easy to check. We start with bivariate spati...
-
作者：Mcelroy, T. S.
摘要：This paper addresses the topic of nonnested time series model comparisons. The main result is a central limit theorem for the likelihood ratio statistic when the models are nonnested and non-equivalent. The concepts of model equivalence and forecast equivalence, which are important for determining the parameter subset corresponding to the null hypothesis, are developed. The method is validated through a simulation study and illustrated on a retail time series.
-
作者：Shao, Jun; Wang, Lei
作者单位：East China Normal University; University of Wisconsin System; University of Wisconsin Madison
摘要：To estimate unknown population parameters based on data having nonignorable missing values with a semiparametric exponential tilting propensity, Kim & Yu (2011) assumed that the tilting parameter is known or can be estimated from external data, in order to avoid the identifiability issue. To remove this serious limitation on the methodology, we use an instrument, i.e., a covariate related to the study variable but unrelated to the missing data propensity, to construct some estimating equations...
-
作者：Tan, Kean Ming; Ning, Yang; Witten, Daniela M.; Liu, Han
摘要：In classical statistics, much thought has been put into experimental design and data collection. In the high-dimensional setting, however, experimental design has been less of a focus. In this paper, we stress the importance of collecting multiple replicates for each subject in the high-dimensional setting. We consider learning the structure of a graphical model with latent variables, under the assumption that these variables take a constant value across replicates within each subject. By coll...
-
作者：Kartsonaki, Christiana; Cox, D. R.
作者单位：University of Oxford; University of Oxford
摘要：A theoretical analysis is made of the properties of various methods for comparing two distributions of survival time. The results are intended primarily to guide the choice of method of analysis for such simple comparisons as of a treatment versus a control, but the main implications are fairly general, illustrating the performance of different models in a range of conditions. For most of the models there is a parameter specifying the comparison of interest and the Fisher information per obser...
