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作者：Delaigle, A.; Hall, P.
作者单位：University of Melbourne
摘要：We consider curve extension and linear prediction for functional data observed only on a part of their domain, in the form of fragments. We suggest an approach based on a combination of Markov chains and nonparametric smoothing techniques, which enables us to extend the observed fragments and construct approximated prediction intervals around them, construct mean and covariance function estimators, and derive a linear predictor. The procedure is illustrated on real and simulated data.
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作者：Guo, Shaojun; Wang, Yazhen; Yao, Qiwei
作者单位：Renmin University of China; University of Wisconsin System; University of Wisconsin Madison; University of London; London School Economics & Political Science
摘要：We consider a class of vector autoregressive models with banded coefficient matrices. This setting represents a type of sparse structure for high-dimensional time series, although the implied auto-covariance matrices are not banded. The structure is also practically meaningful when the component time series are ordered appropriately. We establish the convergence rates of the estimated banded autoregressive coefficient matrices. We also propose a Bayesian information criterion for determining t...
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作者：Luo, Wei; Li, Bing
作者单位：City University of New York (CUNY) System; Baruch College (CUNY); Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
摘要：In applying statistical methods such as principal component analysis, canonical correlation analysis, and sufficient dimension reduction, we need to determine how many eigenvectors of a random matrix are important for estimation. This problem is known as order determination, and amounts to estimating the rank of a matrix. Previous order-determination procedures rely either on the decreasing pattern, or elbow, of the eigenvalues, or on the increasing pattern of the variability in the directions...
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作者：Liu, L.; Hudgens, M. G.; Becker-Dreps, S.
作者单位：University of Minnesota System; University of Minnesota Twin Cities; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina; University of North Carolina Chapel Hill
摘要：We consider inference about the causal effect of a treatment or exposure in the presence of interference, i.e., when one individual's treatment affects the outcome of another individual. In the observational setting where the treatment assignment mechanism is not known, inverse probability-weighted estimators have been proposed when individuals can be partitioned into groups such that there is no interference between individuals in different groups. Unfortunately this assumption, which is some...
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作者：Fang, Fang; Shao, Jun
作者单位：East China Normal University
摘要：Existing methods for handling nonignorable missing data rely on the correct specification of parametric models, which is difficult to check. By utilizing the information carried in an instrument, we propose a novel model selection criterion, called the penalized validation criterion, in the presence of nonignorable nonresponse with unspecified propensity. The proposed method can consistently select the most compact correct parametric model from a group of candidate models if one of the candida...
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作者：Som, Agniva; Hans, Christopher M.; MacEachern, Steven N.
作者单位：Duke University; University System of Ohio; Ohio State University
摘要：The development of prior distributions for Bayesian regression has traditionally been driven by the goal of achieving sensible model selection and parameter estimation. The formalization of properties that characterize good performance has led to the development and popularization of thick-tailed mixtures of g priors such as the Zellner-Siow and hyper-g priors. In this paper we introduce a conditional information asymptotic regime that is motivated by the common data analysis setting where at ...
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作者：Cox, D. R.
作者单位：University of Oxford
摘要：An outline account is given of the work of nine major figures working mostly in the earlier two-thirds of the 20th century. Some comments are included about their personal characteristics.
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作者：Moller, Jesper; Safavimanesh, Farzaneh; Rasmussen, Jakob Gulddahl
作者单位：Aalborg University; Shahid Beheshti University
摘要：The analysis of point patterns with linear structures is of interest in many applications. To detect anisotropy in such patterns, in particular in the case of a columnar structure, we introduce a functional summary statistic, the cylindrical K-function, which is a directional K-function whose structuring element is a cylinder. We further introduce a class of anisotropic Cox point processes, called Poisson line cluster point processes. The points of such a process are random displacements of Po...
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作者：Hiabu, M.; Mammen, E.; Martinez-Miranda, M. D.; Nielsen, J. P.
作者单位：City St Georges, University of London; Ruprecht Karls University Heidelberg
摘要：In this paper, in-sample forecasting is defined as forecasting a structured density to sets where it is unobserved. The structured density consists of one-dimensional in-sample components that identify the density on such sets. We focus on the multiplicative density structure, which has recently been seen as the underlying structure of non-life insurance forecasts. In non-life insurance, the in-sample area is defined as one triangle and the forecasting area as the triangle which, added to the ...
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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...
