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作者：Klockmann, K.; Krivobokova, T.
作者单位：University of Vienna
摘要：A new efficient nonparametric estimator for Toeplitz covariance matrices is proposed. This estimator is based on a data transformation that translates the problem of Toeplitz covariance matrix estimation to the problem of mean estimation in an approximate Gaussian regression. The resulting Toeplitz covariance matrix estimator is positive definite by construction, fully data driven and computationally very fast. Moreover, this estimator is shown to be minimax optimal under the spectral norm for...
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作者：Wang, Shulei; Yuan, Bo; Cai, T. Tony; Li, Hongzhe
作者单位：University of Illinois System; University of Illinois Urbana-Champaign; University of Pennsylvania; University of Pennsylvania
摘要：Phylogenetic association analysis plays a crucial role in investigating the correlation between microbial compositions and specific outcomes of interest in microbiome studies. However, existing methods for testing such associations have limitations related to the assumption of a linear association in high-dimensional settings and the handling of confounding effects. Hence, there is a need for methods capable of characterizing complex associations, including nonmonotonic relationships. This art...
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作者：Jiang, Feiyu; Gao, Hanjia; Shao, Xiaofeng
作者单位：Fudan University; University of Illinois System; University of Illinois Urbana-Champaign
摘要：We propose a novel method for testing serial independence of object-valued time series in metric spaces, which are more general than Euclidean or Hilbert spaces. The proposed method is fully nonparametric, free of tuning parameters and can capture all nonlinear pairwise dependence. The key concept used in this paper is the distance covariance in metric spaces, which is extended to the autodistance covariance for object-valued time series. Furthermore, we propose a generalized spectral density ...
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作者：Thompson, Ryan; Forbes, Catherine S.; Maceachern, Steven N.; Peruggia, Mario
作者单位：Monash University; University System of Ohio; Ohio State University
摘要：Statisticl hypotheses are translations of scientific hypotheses into statements about one or more distributions, often concerning their centre. Tests that assess statistical hypotheses of centre implicitly assume a specific centre, e.g., the mean or median. Yet, scientific hypotheses do not always specify a particular centre. This ambiguity leaves the possibility for a gap between scientific theory and statistical practice that can lead to rejection of a true null. In the face of replicability...
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作者：Cui, Y.; Tchetgen, E. J. Tchetgen
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作者：Wiens, D. P.
作者单位：University of Alberta
摘要：We present a result according to which certain functions of covariance matrices are maximized at scalar multiples of the identity matrix. This is used to show that experimental designs that are optimal under an assumption of independent, homoscedastic responses can be minimax robust, in broad classes of alternate covariance structures. In particular, it can justify the common practice of disregarding possible dependence, or heteroscedasticity, at the design stage of an experiment.
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作者：Lin, Zhexiao; Han, Fang
作者单位：University of California System; University of California Berkeley; University of Washington; University of Washington Seattle
摘要：While researchers commonly use the bootstrap to quantify the uncertainty of an estimator, it has been noticed that the standard bootstrap, in general, does not work for Chatterjee's rank correlation. In this paper, we provide proof of this issue under an additional independence assumption, and complement our theory with simulation evidence for general settings. Chatterjee's rank correlation thus falls into a category of statistics that are asymptotically normal, but bootstrap inconsistent. Val...
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作者：Chan, K. W.; Yau, C. Y.
作者单位：Chinese University of Hong Kong
摘要：Estimation of the time-average variance constant is important for statistical analyses involving dependent data. This problem is difficult as it relies on a bandwidth parameter. Specifically, the optimal choices of the bandwidths of all existing estimators depend on the estimand itself and another unknown parameter that is very difficult to estimate. Thus, optimal variance estimation is unachievable. In this paper, we introduce a concept of converging flat-top kernels for constructing variance...
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作者：Henckel, L.; Buttenschoen, M.; Maathuis, M. H.
作者单位：University College Dublin; University of Oxford; Swiss Federal Institutes of Technology Domain; ETH Zurich
摘要：We consider the efficient estimation of total causal effects in the presence of unmeasured confounding using conditional instrumental sets. Specifically, we consider the two-stage least-squares estimator in the setting of a linear structural equation model with correlated errors that is compatible with a known acyclic directed mixed graph. To set the stage for our results, we characterize the class of linearly valid conditional instrumental sets that yield consistent two-stage least-squares es...
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作者：Bao, Yajie; Huo, Yuyang; Ren, Haojie; Zou, Changliang
作者单位：Shanghai Jiao Tong University; Nankai University
摘要：Conformal inference is a popular tool for constructing prediction intervals. We consider here the scenario of post-selection/selective conformal inference, that is, prediction intervals are reported only for individuals selected from unlabelled test data. To account for multiplicity, we develop a general split conformal framework to construct selective prediction intervals with the false coverage-statement rate control. We first investigate the false coverage rate-adjusted method of in the pre...
