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作者：Song, Wookyeong; Muller, Hans-Georg
作者单位：University of California System; University of California Davis
摘要：There are many open questions pertaining to the statistical analysis of random objects, which are increasingly encountered. A major challenge is the absence of linear operations in such spaces. A basic statistical task is to quantify statistical dispersion or spread. For two measures of dispersion for data objects in geodesic metric spaces, Fr & eacute;chet variance and metric variance, we derive a central limit theorem (CLT) for their joint distribution. This analysis reveals that the Alexand...
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作者：Lu, Xin; Wang, Yuhao; Zhang, Zhiheng
作者单位：Washington University (WUSTL); Tsinghua University; Shanghai Qi Zhi Institute; Shanghai University of Finance & Economics; Shanghai University of Finance & Economics
摘要：Randomized experiments are the gold standard for causal inference. However, traditional assumptions, such as the Stable Unit Treatment Value Assumption (SUTVA), often fail in real-world settings where interference between units is present. Network interference, in particular, has garnered significant attention. Structural models, like the linear-in-means model, are commonly used to describe interference, but they rely on the correct specification of the model, which can be restrictive. Recent ...
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作者：Liu, Jiamin; Lian, Heng
作者单位：University of Science & Technology Beijing; City University of Hong Kong; Shenzhen Research Institute, City University of Hong Kong; City University of Hong Kong
摘要：We consider robust conditional mean learning in the mathematical framework of reproducing kernel Hilbert spaces, assuming the errors can be heavy-tailed and at the same time some responses are subject to arbitrary contamination. Simultaneous robustness to both heavy tails and contamination are of interest. When there is no contamination, we establish rates when the (1+theta) -moment (theta>0) of the error exists, which matches the minimax rate for the least squares regression as soon as theta ...
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作者：Kong, Deru; Yu, Ping; Tong, Tiejun; Wang, WenWu
作者单位：University of Hong Kong; Hong Kong Baptist University
摘要：With advances in modern data collection technologies, functional data are increasingly received in a streaming manner. Although numerous methods have been developed to model such data, most focus on estimating the mean and covariance functions, while giving limited attention to their derivatives. In this article, we introduce an online method for estimating the change rates of the mean and covariance functions, enabling real-time updates with high statistical efficiency. The method dynamically...
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作者：Zhou, Yang; Yang, Jin; Yao, Fang
作者单位：Beijing Normal University; Hong Kong Polytechnic University; Peking University
摘要：For covariance test in functional data analysis, existing methods are developed only for fully observed curves, whereas in practice, trajectories are typically observed discretely and with noise. To bridge this gap, we employ a pool-smoothing strategy to construct an FPC-based test statistic, allowing the number of estimated eigenfunctions to grow with the sample size. This yields a consistently nonparametric test, while the challenge arises from the concurrence of diverging truncation and dis...
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作者：Su, Buxin; Zhang, Jiayao; Collina, Natalie; Yan, Yuling; Li, Didong; Cho, Kyunghyun; Fan, Jianqing; Roth, Aaron; Su, Weijie
作者单位：University of Pennsylvania; University of Wisconsin System; University of Wisconsin Madison; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine; New York University; Princeton University
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作者：Chen, Qihui
作者单位：The Chinese University of Hong Kong, Shenzhen
摘要：This article presents a general framework for estimating high-dimensional conditional latent factor models via constrained nuclear norm regularization. We establish large sample properties of the estimators and provide efficient algorithms for their computation. To improve practical applicability, we propose a cross-validation procedure for selecting the regularization parameter. Our framework unifies the estimation of various conditional factor models, enabling the derivation of new asymptoti...
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作者：Tang, Yifu; Kirch, Claudia; Lee, Jeong Eun; Meyer, Renate
作者单位：University of Otago; Otto von Guericke University; University of Auckland
摘要：Stationarity plays a pivotal role in time series analysis. It is not only the basis for the derivation of general asymptotic theory but it also allows an efficient analysis in the frequency domain via the Whittle likelihood, based on the asymptotic independence of the Fourier coefficients. However, many regularly sampled data derived from the observation of physical or ecological processes, for instance, are only locally stationary. They exhibit slowly evolving spectra and asymptotically non-v...
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作者：Chen, Liujun; Zhou, Chen
作者单位：Chinese Academy of Sciences; University of Science & Technology of China, CAS; Erasmus University Rotterdam; Erasmus University Rotterdam - Excl Erasmus MC
摘要：When applying multivariate extreme value statistics to analyze tail risk in compound events defined by a multivariate random vector, one often assumes that all dimensions share the same extreme value index. While such an assumption can be tested using a Wald-type test, the performance of such a test deteriorates as the dimensionality increases. This article introduces novel tests for comparing extreme value indices in high-dimensional settings, under both weak and general cross-sectional tail ...
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作者：Champon, Xiaoxia; Staicu, Ana-Maria; Weishampel, Anthony; Jayalath, Chathura; Rand, William
作者单位：North Carolina State University; State University System of Florida; University of Central Florida; North Carolina State University
摘要：Social media provides more insight into consumer behavior than companies have ever had, and firms can interact with consumers on social media to increase their brand loyalty and address concerns they might have. However, it is critical for companies to evaluate whether the consumers they interact with have the potential to positively promote the firm. This can be challenging, especially when limited information is available about social media users. Our work proposes a flexible methodology to ...
