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作者：Wakefield, Jon; Simpson, Daniel; Godwin, Jessica
作者单位：University of Washington; University of Washington Seattle; University of Washington; University of Washington Seattle; University of Bath
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作者：Zhang, Ning; Apley, Daniel W.
作者单位：Northwestern University
摘要：Gaussian process modeling, or kriging, is a popular method for modeling data from deterministic computer simulations, and the most common choices of covariance function are Gaussian, power exponential, and Matern. A characteristic of these covariance functions is that the basis functions associated with their corresponding response predictors are localized, in the sense that they decay to zero as the input location moves away from the simulated input sites. As a result, the predictors tend to ...
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作者：Pena, Daniel; Yohai, Victor J.
摘要：Brillinger defined dynamic principal components (DPC) for time series based on a reconstruction criterion. He gave a very elegant theoretical solution and proposed an estimator which is consistent under stationarity. Here, we propose a new enterally empirical approach to DPC. The main differences with the existing methods mainly Brillinger procedure are (1) the DPC we propose need not be a linear combination of the observations and (2) it can be based on a variety of loss functions including r...
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作者：Cheng, Ming-Yen; Honda, Toshio; Zhang, Jin-Ting
作者单位：National Taiwan University; Hitotsubashi University; National University of Singapore
摘要：Varying coefficient models have numerous applications in a wide scope of scientific areas. While enjoying nice interpretability, they also allow for flexibility in modeling dynamic impacts of the covariates. But, in the new era of big data, it is challenging to select the relevant variables when the dimensionality is very large. Recently, several works are focused on this important problem based on sparsity assumptions; they are subject to some limitations, however. We introduce an appealing f...
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作者：Li, Gang; Yang, Qing
作者单位：University of California System; University of California Los Angeles; Duke University
摘要：This article develops joint inferential methods for,the cause-specific hazard function and the cumulative incidence function of a specific type of failure to assess the effects of a variable on the time to the type of failure of interest in the presence of competing risks. Joint inference for the two functions are needed in practice because (i) they describe different characteristics of a given type of failure, (ii) they do not uniquely determine each other, and (iii) the effects of a variable...
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作者：Xu, Yanxun; Muller, Peter; Wahed, Abdus S.; Thall, Peter F.
作者单位：University of Texas System; University of Texas Austin; University of Texas System; University of Texas Austin; Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh; University of Texas System; UTMD Anderson Cancer Center
摘要：We analyze a dataset arising from a clinical trial involving multi-stage chemotherapy regimes for acute leukemia. The trial design was a 2 x 2 factorial for frontline therapies only. Motivated, by the idea that subsequent salvage treatments affect survival time, we model therapy as a dynamic treatment regime (DTR), that is, an alternating sequence of adaptive treatments or other actions and transition times between disease states. These sequences may vary substantially between patients, depend...
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作者：Zhou, Mingyuan; Padilla, Oscar Hernan Madrid; Scott, James G.
作者单位：University of Texas System; University of Texas Austin; University of Texas System; University of Texas Austin
摘要：We define a family of probability distributions for random count matrices with a potentially unbounded number of rows and columns. The three distributions we consider are derived from the gamma-Poisson, gamma-negative binomial, and beta-negative binomial processes, which we refer to generically as a family of negative-binomial processes. Because the models lead to closed-form update equations within the context of a Gibbs sampler, they are natural candidates for nonparametric Bayesian priors o...
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作者：Quintana, Fernando A.; Johnson, Wesley O.; Waetjen, L. Elaine; Gold, Ellen B.
作者单位：Pontificia Universidad Catolica de Chile; University of California System; University of California Irvine; University of California System; University of California Davis; University of California System; University of California Davis
摘要：Practical Bayesian nonparametric methods have been developed across a wide variety of contexts. Here, we develop a novel statistical model that generalizes standard mixed models for longitudinal data that include flexible mean functions as well as combined compound symmetry (CS) and autoregressive (AR) covariance structures. AR structure is often specified through the use of a Gaussian process (GP) with covariance functions that allow longitudinal data to be more correlated if they are observe...
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作者：Wang, Junhui; Shen, Xiaotong; Sun, Yiwen; Qu, Annie
作者单位：University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital; City University of Hong Kong; University of Minnesota System; University of Minnesota Twin Cities; University of Illinois System; University of Illinois Urbana-Champaign
摘要：Unstructured data refer to information that lacks certain structures and cannot be organized in a predefined fashion. Unstructured data often involve words, texts, graphs, objects, or multimedia types of files that are difficult to process and analyze with traditional computational tools and statistical methods. This work explores ordinal classification for unstructured predictors with ordered class categories, where imprecise information concerning strengths of association between predictors ...
