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作者：Lin, Z.; Muller, H. G.; Park, B. U.
作者单位：National University of Singapore; University of California System; University of California Davis; Seoul National University (SNU)
摘要：We propose and investigate an additive regression model for symmetric positive-definite matrix-valued responses and multiple scalar predictors. The model exploits the Abelian group structure inherited from either of the log-Cholesky and log-Euclidean frameworks for symmetric positive-definite matrices and naturally extends to general Abelian Lie groups. The proposed additive model is shown to connect to an additive model on a tangent space. This connection not only entails an efficient algorit...
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作者：Lu, Zitong; Geng, Zhi; Li, Wei; Zhu, Shengyu; Jia, Jinzhu
作者单位：Peking University; Beijing Technology & Business University; Renmin University of China; Renmin University of China; Huawei Technologies; Peking University; Peking University
摘要：For the case with a single causal variable, Dawid et al. (2014) defined the probability of causation, and Pearl (2000) defined the probability of necessity to assess the causes of effects. For a case with multiple causes that could affect each other, this paper defines the posterior total and direct causal effects based on the evidence observed for post-treatment variables, which could be viewed as measurements of causes of effects. Posterior causal effects involve the probabilities of counter...
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作者：Yu, Long; Xie, Jiahui; Zhou, Wang
作者单位：Shanghai University of Finance & Economics; National University of Singapore
摘要：The Kronecker product covariance structure provides an efficient way to model the inter-correlations of matrix-variate data. In this paper, we propose test statistics for the Kronecker product covariance matrix based on linear spectral statistics of renormalized sample covariance matrices. A central limit theorem is proved for the linear spectral statistics, with explicit formulas for the mean and covariance functions, thereby filling a gap in the literature. We then show theoretically that th...
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作者：Kovacs, S.; Buehlmann, P.; Li, H.; Munk, A.
作者单位：Swiss Federal Institutes of Technology Domain; ETH Zurich; University of Gottingen
摘要：We propose seeded binary segmentation for large-scale changepoint detection problems. We construct a deterministic set of background intervals, called seeded intervals, in which single changepoint candidates are searched for. The final selection of changepoints based on these candidates can be done in various ways, adapted to the problem at hand. The method is thus easy to adapt to many changepoint problems, ranging from univariate to high dimensional. Compared to recently popular random backg...
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作者：Hu, Jianhua; Huang, Jian; Liu, Xiaoqian; Liu, Xu
作者单位：Shanghai University of Finance & Economics; Hong Kong Polytechnic University; York University - Canada
摘要：This article investigates the statistical problem of response-variable selection with high-dimensional response variables and a diverging number of predictor variables with respect to the sample size in the framework of multivariate linear regression. A response best-subset selection model is proposed by introducing a 0-1 selection indicator for each response variable, and then a response best-subset selector is developed by introducing a separation parameter and a novel penalized least-square...
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作者：Koning, N. W.; Hemerik, J.
作者单位：Erasmus University Rotterdam; Erasmus University Rotterdam - Excl Erasmus MC; Wageningen University & Research
摘要：We consider testing invariance of a distribution under an algebraic group of transformations, such as permutations or sign flips. As such groups are typically huge, tests based on the full group are often computationally infeasible. Hence, it is standard practice to use a random subset of transformations. We improve upon this by replacing the random subset with a strategically chosen, fixed subgroup of transformations. In a generalized location model, we show that the resulting tests are often...
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作者：Mccormack, A.; Hoff, P. D.
作者单位：Duke University
摘要：The Frechet mean generalizes the concept of a mean to a metric space setting. In this work we consider equivariant estimation of Frechet means for parametric models on metric spaces that are Riemannian manifolds. The geometry and symmetry of such a space are partially encoded by its isometry group of distance-preserving transformations. Estimators that are equivariant under the isometry group take into account the symmetry of the metric space. For some models, there exists an optimal equivaria...
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作者：Liu, Hanzhong; Tu, Fuyi; Ma, Wei
作者单位：Tsinghua University; Renmin University of China
摘要：We consider the problem of estimating and inferring treatment effects in randomized experiments. In practice, stratified randomization, or more generally, covariate-adaptive randomization, is routinely used in the design stage to balance treatment allocations with respect to a few variables that are most relevant to the outcomes. Then, regression is performed in the analysis stage to adjust the remaining imbalances to yield more efficient treatment effect estimators. Building upon and unifying...
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作者：Wang, J.; Wang, H.; Cheng, K.
作者单位：University of Connecticut
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作者：Jiang, Zhichao; Chen, Shizhe; Ding, Peng
作者单位：Sun Yat Sen University; University of California System; University of California Davis; University of California System; University of California Berkeley
摘要：Point processes are probabilistic tools for modelling event data. While there exists a fast-growing literature on the relationships between point processes, how such relationships connect to causal effects remains unexplored. In the presence of unmeasured confounders, parameters from point process models do not necessarily have causal interpretations. We propose an instrumental variable method for causal inference with point process treatment and outcome. We define causal quantities based on p...
