-
作者：Sarkar, Soham; Panaretos, Victor M.
作者单位：Indian Statistical Institute; Indian Statistical Institute Delhi; Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne
摘要：Covariance estimation is ubiquitous in functional data analysis. Yet, the case of functional observations over multidimensional domains introduces computational and statistical challenges, rendering the standard methods effectively inapplicable. To address this problem, we introduce Covariance Networks (CovNet) as a modelling and estimation tool. The CovNet model is universal-it can be used to approximate any covariance up to desired precision. Moreover, the model can be fitted efficiently to ...
-
作者：Walther, Guenther; Perry, Andrew
作者单位：Stanford University
摘要：We consider the problem of detecting an elevated mean on an interval with unknown location and length in the univariate Gaussian sequence model. Recent results have shown that using scale-dependent critical values for the scan statistic allows to attain asymptotically optimal detection simultaneously for all signal lengths, thereby improving on the traditional scan, but this procedure has been criticised for losing too much power for short signals. We explain this discrepancy by showing that t...
-
作者：Han, Rungang; Luo, Yuetian; Wang, Miaoyan; Zhang, Anru R.
作者单位：University of Wisconsin System; University of Wisconsin Madison; Duke University; Duke University; Duke University; Duke University
摘要：High-order clustering aims to identify heterogeneous substructures in multiway datasets that arise commonly in neuroimaging, genomics, social network studies, etc. The non-convex and discontinuous nature of this problem pose significant challenges in both statistics and computation. In this paper, we propose a tensor block model and the computationally efficient methods, high-order Lloyd algorithm (HLloyd), and high-order spectral clustering (HSC), for high-order clustering. The convergence gu...
-
作者：Karmakar, Bikram
作者单位：State University System of Florida; University of Florida
摘要：Blocked randomized designs are used to improve the precision of treatment effect estimates compared to a completely randomized design. A block is a set of units that are relatively homogeneous and consequently would tend to produce relatively similar outcomes if the treatment had no effect. The problem of finding the optimal blocking of the units into equal sized blocks of any given size larger than two is known to be a difficult problem-there is no polynomial time method guaranteed to find th...
-
作者：Jewson, Jack; Rossell, David
作者单位：Pompeu Fabra University; Barcelona School of Economics
摘要：Statisticians often face the choice between using probability models or a paradigm defined by minimising a loss function. Both approaches are useful and, if the loss can be re-cast into a proper probability model, there are many tools to decide which model or loss is more appropriate for the observed data, in the sense of explaining the data's nature. However, when the loss leads to an improper model, there are no principled ways to guide this choice. We address this task by combining the Hyva...
-
作者：Le, Can M.; Li, Tianxi
作者单位：University of California System; University of California Davis; University of Virginia
摘要：Linear regression on network-linked observations has been an essential tool in modelling the relationship between response and covariates with additional network structures. Previous methods either lack inference tools or rely on restrictive assumptions on social effects and usually assume that networks are observed without errors. This paper proposes a regression model with non-parametric network effects. The model does not assume that the relational data or network structure is exactly obser...
