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作者：Li, Fan; Morgan, Kari Lock; Zaslavsky, Alan M.
作者单位：Duke University; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Harvard University; Harvard Medical School
摘要：Covariate balance is crucial for unconfounded descriptive or causal comparisons. However, lack of balance is common in observational studies. This article considers weighting strategies for balancing covariates. We define a general class of weightsthe balancing weightsthat balance the weighted distributions of the covariates between treatment groups. These weights incorporate the propensity score to weight each group to an analyst-selected target population. This class unifies existing weighti...
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作者：Shi, Peng; Yang, Lu
作者单位：University of Wisconsin System; University of Wisconsin Madison; University of Amsterdam
摘要：In nonlife insurance, insurers use experience rating to adjust premiums to reflect policyholders' previous claim experience. Performing prospective experience rating can be challenging when the claim distribution is complex. For instance, insurance claims are semicontinuous in that a fraction of zeros is often associated with an otherwise positive continuous outcome from a right-skewed and long-tailed distribution. Practitioners use credibility premium that is a special form of the shrinkage e...
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作者：Wang, Yuanjia; Fu, Haoda; Zeng, Donglin
作者单位：Columbia University; Eli Lilly; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine
摘要：Individualized medical decision making is often complex due to patient treatment response heterogeneity. Pharmacotherapy may exhibit distinct efficacy and safety profiles for different patient populations. An optimal treatment that maximizes clinical benefit for a patient may also lead to concern of safety due to a high risk of adverse events. Thus, to guide individualized clinical decision making and deliver optimal tailored treatments, maximizing clinical benefit should be considered in the ...
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作者：Hero, Alfred
作者单位：University of Michigan System; University of Michigan
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作者：Chen, Zhao; Fan, Jianqing; Li, Runze
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Fudan University; Princeton University; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
摘要：Error variance estimation plays an important role in statistical inference for high-dimensional regression models. This article concerns with error variance estimation in high-dimensional sparse additive model. We study the asymptotic behavior of the traditional mean squared errors, the naive estimate of error variance, and show that it may significantly underestimate the error variance due to spurious correlations that are even higher in nonparametric models than linear models. We further pro...
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作者：Kuhnert, Petra M.
作者单位：Commonwealth Scientific & Industrial Research Organisation (CSIRO); CSIRO Data61
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作者：DeYoreo, Maria; Kottas, Athanasios
作者单位：RAND Corporation; Duke University; University of California System; University of California Santa Cruz
摘要：We develop a Bayesian nonparametric framework for modeling ordinal regression relationships, which evolve in discrete time. The motivating application involves a key problem in fisheries research on estimating dynamically evolving relationships between age, length, and maturity, the latter recorded on an ordinal scale. The methodology builds from nonparametric mixture modeling for the joint stochastic mechanism of covariates and latent continuous responses. This approach yields highly flexible...
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作者：Hardt, Moritz
作者单位：University of California System; University of California Berkeley
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作者：Jiang, Jiming; Rao, J. Sunil; Fan, Jie; Thuan Nguyen
作者单位：University of California System; University of California Davis; University of Miami; Oregon Health & Science University
摘要：Many practical problems are related to prediction, where the main interest is at subject (e.g., personalized medicine) or (small) sub-population (e.g., small community) level. In such cases, it is possible to make substantial gains in prediction accuracy by identifying a class that a new subject belongs to. This way, the new subject is potentially associated with a random effect corresponding to the same class in the training data, so that method of mixed model prediction can be used to make t...
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作者：Xia, Yin; Cai, Tianxi; Cai, T. Tony
作者单位：Fudan University; Harvard University; Harvard T.H. Chan School of Public Health; University of Pennsylvania
摘要：Making accurate inference for gene regulatory networks, including inferring about pathway-by-pathway interactions, is an important and difficult task. Motivated by such genomic applications, we consider multiple testing for conditional dependence between subgroups of variables. Under a Gaussian graphical model framework, the problem is translated into simultaneous testing for a collection of submatrices of a high-dimensional precision matrix with each submatrix summarizing the dependence struc...
