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作者：Ba, Shan; Joseph, V. Roshan
作者单位：University System of Georgia; Georgia Institute of Technology
摘要：Space-filling designs such as Latin hypercube designs (LHDs) are widely used in computer experiments. However, finding an optimal LHD with good space-filling properties is computationally cumbersome. On the other hand, the well-established factorial designs in physical experiments are unsuitable for computer experiments owing to the redundancy of design points when projected onto a subset of factor space. In this work, we present a new class of space-filling designs developed by splitting two-...
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作者：Polonik, Wolfgang
作者单位：University of California System; University of California Davis
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作者：Ghosh, Joyee; Clyde, Merlise A.
作者单位：University of Iowa; Duke University
摘要：Choosing the subset of covariates to use in regression or generalized linear models is a ubiquitous problem. The Bayesian paradigm addresses the problem of model uncertainty by considering models corresponding to all possible subsets of the covariates, where the posterior distribution over models is used to select models or combine them via Bayesian model averaging (BMA). Although conceptually straightforward, BMA is often difficult to implement in practice, since either the number of covariat...
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作者：Wei, Susan; Nobel, Andrew B.
作者单位：University of North Carolina; University of North Carolina Chapel Hill
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作者：Zhang, Hao Helen; Cheng, Guang; Liu, Yufeng
作者单位：North Carolina State University; University of Arizona; Purdue University System; Purdue University; University of North Carolina; University of North Carolina Chapel Hill
摘要：Partially linear models provide a useful class of tools for modeling complex data by naturally incorporating a combination of linear and nonlinear effects within one framework. One key question in partially linear models is the choice of model structure, that is, how to decide which covariates are linear and which are nonlinear. This is a fundamental, yet largely unsolved problem for partially linear models. In practice, one often assumes that the model structure is given or known and then mak...
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作者：Breitung, Joerg; Tenhofen, Joern
作者单位：University of Bonn; Deutsche Bundesbank
摘要：In this article a simple two-step estimation procedure of the dynamic factor model is proposed. The estimator allows for heteroscedastic and serially correlated errors. It turns out that the feasible two-step estimator has the same limiting distribution as the generalized least squares (GLS) estimator assuming that the covariance parameters are known. In a Monte Carlo study of the small sample properties, we find that the GLS estimators may be substantially more efficient than the usual estima...
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作者：Kuan, Pei Fen; Chung, Dongjun; Pan, Guangjin; Thomson, James A.; Stewart, Ron; Keles, Suenduez
作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of Wisconsin System; University of Wisconsin Madison; University of Wisconsin System; University of Wisconsin Madison; Chinese Academy of Sciences; Guangzhou Institute of Biomedicine & Health, CAS; Chinese Academy of Sciences; University of Wisconsin System; University of Wisconsin Madison; University of Wisconsin System; University of Wisconsin Madison; The Morgridge Institute for Research, Inc.
摘要：Chromatin immunoprecipitation followed by sequencing (ChIP-Seq) has revolutionalized experiments for genome-wide profiling of DNA-binding proteins, histone modifications, and nucleosome occupancy. As the cost of sequencing is decreasing, many researchers are switching from microarray-based technologies (ChIP-chip) to ChIP-Seq for genome-wide study of transcriptional regulation. Despite its increasing and well-deserved popularity, there is little work that investigates and accounts for sources ...
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作者：Lee, Seonjoo; Shen, Haipeng; Truong, Young; Lewis, Mechelle; Huang, Xuemei
作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina; University of North Carolina Chapel Hill; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Penn State Health; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Penn State Health
摘要：Independent component analysis (ICA) is an effective data-driven method for blind source separation. It has been successfully applied to separate source signals of interest from their mixtures. Most existing ICA procedures are carried out by relying solely on the estimation of the marginal density functions, either parametrically or nonparametrically. In many applications, correlation structures within each source also play an important role besides the marginal distributions. One important ex...
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作者：Frees, Edward W.; Meyers, Glenn; Cummings, A. David
作者单位：University of Wisconsin System; University of Wisconsin Madison
摘要：Individuals, corporations and government entities regularly exchange financial risks y at prices Pi. Comparing distributions of risks and prices can be difficult, particularly when the financial risk distribution is complex. For example, with insurance, it is not uncommon for a risk distribution to be a mixture of 0's (corresponding to no claims) and a right-skewed distribution with thick tails (the claims distribution). However, analysts do not work in a vacuum, and in the case of insurance t...
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作者：Zhu, Hongxiao; Brown, Philip J.; Morris, Jeffrey S.
作者单位：University of Kent; University of Texas System; UTMD Anderson Cancer Center
摘要：Functional data are increasingly encountered in scientific studies, and their high dimensionality and complexity lead to many analytical challenges. Various methods for functional data analysis have been developed, including functional response regression methods that involve regression of a functional response on univariate/multivariate predictors with nonparametrically represented functional coefficients. In existing methods, however, the functional regression can be sensitive to outlying cu...
