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作者：Battey, H. S.; Mccullagh, Peter
作者单位：Imperial College London; University of Chicago
摘要：It is frequently observed in practice that the Wald statistic gives a poor assessment of the statistical significance of a variance component. This paper provides detailed analytic insight into the phenomenon by way of two simple models, which point to an atypical geometry as the source of the aberration. The latter can in principle be checked numerically to cover situations of arbitrary complexity, such as those arising from elaborate forms of blocking in an experimental context, or models fo...
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作者：Zhou, Ying; Tang, Dingke; Kong, Dehan; Wang, Linbo
作者单位：University of Connecticut; University of Toronto
摘要：A key challenge in causal inference from observational studies is the identification and estimation of causal effects in the presence of unmeasured confounding. In this paper, we introduce a novel approach for causal inference that leverages information in multiple outcomes to deal with unmeasured confounding. An important assumption in our approach is conditional independence among multiple outcomes. In contrast to existing proposals in the literature, the roles of multiple outcomes in the co...
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作者：Li, Yicheng; Zhang, Haobo; Lin, Qian
作者单位：Tsinghua University
摘要：One of the most interesting problems in the recent renaissance of the studies in kernel regression might be whether kernel interpolation can generalize well, since it may help us understand the 'benign overfitting phenomenon' reported in the literature on deep networks. In this paper, under mild conditions, we show that, for any epsilon>0, the generalization error of kernel interpolation is lower bounded by Omega(n(-epsilon)). In other words, the kernel interpolation generalizes poorly for a l...
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作者：Wang, J. Y.; Ye, Z. S.; Chen, Y.
作者单位：National University of Singapore; University of Pennsylvania
摘要：Likelihood-based inference under nonconvex constraints on model parameters has become increasingly common in biomedical research. In this paper, we establish large-sample properties of the maximum likelihood estimator when the true parameter value lies at the boundary of a nonconvex parameter space. We further derive the asymptotic distribution of the likelihood ratio test statistic under nonconvex constraints on model parameters. A general Monte Carlo procedure for generating the limiting dis...
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作者：Cape, J.
作者单位：University of Wisconsin System; University of Wisconsin Madison
摘要：Varimax factor rotations, while popular among practitioners in psychology and statistics since being introduced by , have historically been viewed with skepticism and suspicion by some theoreticians and mathematical statisticians. Now, work by provides new, fundamental insight: varimax rotations provably perform statistical estimation in certain classes of latent variable models when paired with spectral-based matrix truncations for dimensionality reduction. We build on this new-found understa...
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作者：Gui, Yu; Hore, Rohan; Ren, Zhimei; Barber, Rina Foygel
作者单位：University of Chicago; University of Pennsylvania
摘要：This paper introduces an assumption-lean method that constructs valid and efficient lower predictive bounds for survival times with censored data. We build on recent work by Cand & egrave;s et al. (2023), whose approach first subsets the data to discard any data points with early censoring times and then uses a reweighting technique, namely, weighted conformal inference (Tibshirani et al., 2019), to correct for the distribution shift introduced by this subsetting procedure. For our new method,...
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作者：Aue, Alexander; Burman, Prabir
作者单位：University of California System; University of California Davis
摘要：The accurate estimation of prediction errors in time series is an important problem, which has immediate implications for the accuracy of prediction intervals as well as the quality of a number of widely used time series model selection criteria such as the Akaike information criterion. Except for simple cases, however, it is difficult or even impossible to obtain exact analytical expressions for one-step and multi-step predictions. This may be one of the reasons that, unlike in the independen...
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作者：Cronie, Ottmar; Moradi, Mehdi; Biscio, Christophe A. N.
作者单位：Chalmers University of Technology; Umea University; Aalborg University
摘要：Motivated by the general ability of cross-validation to reduce overfitting and mean square error, we develop a cross-validation-based statistical theory for general point processes. It is based on the combination of two novel concepts for general point processes: cross-validation and prediction errors. Our cross-validation approach uses thinning to split a point process/pattern into pairs of training and validation sets, while our prediction errors measure discrepancy between two point process...
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作者：Goeman, Jelle J.; Solari, Aldo
作者单位：Leiden University - Excl LUMC; Leiden University; Leiden University Medical Center (LUMC); University of Milano-Bicocca
摘要：We investigate a class of methods for selective inference that condition on a selection event. Such methods follow a two-stage process. First, a data-driven collection of hypotheses is chosen from some large universe of hypotheses. Subsequently, inference takes place within this data-driven collection, conditioned on the information that was used for the selection. Examples of such methods include basic data splitting as well as modern data-carving methods and post-selection inference methods ...
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作者：Li, Wei; Lu, Zitong; Jia, Jinzhu; Xie, Min; Geng, Zhi
作者单位：Renmin University of China; Renmin University of China; City University of Hong Kong; Peking University; Peking University; Beijing Technology & Business University
摘要：As highlighted in and , deducing the causes of given effects is a more challenging problem than evaluating the effects of causes in causal inference. proposed an approach for deducing causes of a single effect variable based on posterior causal effects. In many applications, there are multiple effect variables, and they can be used simultaneously to more accurately deduce the causes. To retrospectively deduce causes from multiple effects, we propose multivariate posterior total, intervention a...
