2期

最新文章

• On the partial autocorrelation function for locally stationary time series: characterization, estimation and inference AI翻译
  作者：Ding, Xiucai; Zhou, Zhou
  作者单位：University of California System; University of California Davis; University of Toronto
  摘要：For stationary time series, it is common to use plots of the partial autocorrelation function (PACF) or PACF-based tests to explore the temporal dependence structure of the process. To the best of our knowledge, analogues for nonstationary time series have not yet been fully developed. This article aims to fill this gap for locally stationary time series with short-range dependence. First, we characterize the PACF locally in the time domain and show that the jth PACF decays with j at a rate th...
• Semiparametric sieve estimation for survival data with two-layer censoring AI翻译
  作者：Wang, Yudong; Tong, Jiayi; Hu, Xiangbin; Ye, Zhi-Sheng; Tang, Cheng Yong; Chen, Yong
  作者单位：National University of Singapore; University of Pennsylvania; Pennsylvania Commonwealth System of Higher Education (PCSHE); Temple University
  摘要：Disease registry data provide important information on the progression of disease conditions. However, reports of death or drop-out of patients enrolled in the registry are always subject to a noticeable delay. Reporting delays, together with the administrative censoring that arises from a freeze date in data collection, lead to two layers of right censoring in the data. The first layer results from random drop-out and acts on the survival time. The second layer is the administrative censoring...
• Assessing variable importance in survival analysis using machine learning AI翻译
  作者：Wolock, C. J.; Gilbert, P. B.; Simon, N.; Carone, M.
  作者单位：University of Pennsylvania; Fred Hutchinson Cancer Center; University of Washington; University of Washington Seattle
  摘要：Given a collection of features available for inclusion in a predictive model, it may be of interest to quantify the relative importance of a subset of features for the prediction task at hand. For example, in HIV vaccine trials, participant baseline characteristics are used to predict the probability of HIV acquisition over the intended follow-up period, and investigators may wish to understand how much certain types of predictors, such as behavioural factors, contribute to overall predictiven...
• Bayesian clustering of high-dimensional data via latent repulsive mixtures AI翻译
  作者：Ghilotti, L.; Beraha, M.; Guglielmi, A.
  作者单位：University of Milano-Bicocca; Polytechnic University of Milan
  摘要：Model-based clustering of moderate- or large-dimensional data is notoriously difficult. We propose a model for simultaneous dimensionality reduction and clustering by assuming a mixture model for a set of latent scores, which are then linked to the observations via a Gaussian latent factor model. This approach was recently investigated by Chandra et al. (2023). The authors used a factor-analytic representation and assumed a mixture model for the latent factors. However, performance can deterio...
• Two-sample distribution tests in high dimensions via max-sliced Wasserstein distance and bootstrapping AI翻译
  作者：Hu, Xiaoyu; Lin, Zhenhua
  作者单位：Xi'an Jiaotong University; National University of Singapore
  摘要：Two-sample hypothesis testing is a fundamental statistical problem for inference about two populations. In this paper, we construct a novel test statistic to detect high-dimensional distributional differences based on the max-sliced Wasserstein distance to mitigate the curse of dimensionality. By exploiting an intriguing link between the distance and suprema of empirical processes, we develop an effective bootstrapping procedure to approximate the null distribution of the test statistic. One d...
• The only admissible way of merging arbitrary e-values AI翻译
  作者：Wang, Ruodu
  作者单位：University of Waterloo
  摘要：In this paper it is proved that the only admissible way of merging arbitrary $ e $-values is to use a weighted arithmetic average. This result completes the picture of merging methods for arbitrary $ e $-values and generalizes the result of that the only admissible way of symmetrically merging $ e $-values is to use the arithmetic average combined with a constant. Although the proved statement is naturally anticipated, its proof relies on a sophisticated application of optimal transport dualit...
• Anytime-valid and asymptotically efficient inference driven by predictive recursion AI翻译
  作者：Dixit, Vaidehi; Martin, Ryan
  作者单位：University of Missouri System; University of Missouri Columbia; North Carolina State University
  摘要：Distinguishing two models is a fundamental and practically important statistical problem. Error rate control is crucial to the testing logic, but in complex nonparametric settings can be difficult to achieve, especially when the stopping rule that determines the data collection process is not available. This paper proposes an $ e $-process construction based on the predictive recursion algorithm originally designed to recursively fit nonparametric mixture models. The resulting predictive recur...
• On the fundamental limitations of multi-proposal Markov chain Monte Carlo algorithms AI翻译
  作者：Pozza, F.; Zanella, G.
  作者单位：Bocconi University
  摘要：We study multi-proposal Markov chain Monte Carlo algorithms, such as multiple-try or generalized Metropolis-Hastings schemes, which have recently received renewed attention due to their amenability to parallel computing. First, we prove that no multi-proposal scheme can speed up convergence relative to the corresponding single-proposal scheme by more than a factor of $ K $, where $ K $ denotes the number of proposals at each iteration. This result applies to arbitrary target distributions and ...
• Large-scale multiple testing of composite null hypotheses under heteroskedasticity AI翻译
  作者：Gang, B.; Banerjee, T.
  作者单位：Fudan University; University of Kansas
  摘要：Heteroskedasticity poses several methodological challenges in designing valid and powerful procedures for simultaneous testing of composite null hypotheses. In particular, the conventional practice of standardizing or rescaling heteroskedastic test statistics in this setting may severely affect the power of the underlying multiple testing procedure. Additionally, when the inferential parameter of interest is correlated with the variance of the test statistic, methods that ignore this dependenc...
• Improving randomized controlled trial analysis via data-adaptive borrowing AI翻译
  作者：Gao, Chenyin; Yang, Shu; Shan, Mingyang; Ye, Wenyu; Lipkovich, Ilya; Faries, Douglas
  作者单位：North Carolina State University; Eli Lilly; Lilly Research Laboratories
  摘要：In recent years, real-world external controls have grown in popularity as a tool to empower randomized placebo-controlled trials, particularly in rare diseases or cases where balanced randomization is unethical or impractical. However, as external controls are not always comparable to the trials, direct borrowing without scrutiny may heavily bias the treatment effect estimator. Our paper proposes a data-adaptive integrative framework capable of preventing unknown biases of the external control...