Journal of the Royal Statistical Society: Series B

最新文章

• A unified generalization of the inverse regression methods via column selection AI翻译
  作者：Jin, Yin; Luo, Wei
  作者单位：Zhejiang University
  摘要：A bottleneck of sufficient dimension reduction (SDR) in the modern era is that, among numerous methods, only sliced inverse regression (SIR) is generally applicable in high-dimensional settings. The higher-order inverse regression methods, which form a major family of SDR methods superior to SIR at the population level, suffer from the dimensionality of their intermediate matrix-valued parameters which have excessive columns. In this paper, we propose to use a small subset of columns of the ma...
• An optimal design framework for lasso sign recovery AI翻译
  作者：Stallrich, Jonathan W.; Young, Kade; Weese, Maria L.; Smucker, Byran J.; Edwards, David J.
  作者单位：North Carolina State University; University System of Ohio; Miami University; University System of Ohio; Miami University; Henry Ford Health System; Henry Ford Health System; Michigan State University; Michigan State University College of Human Medicine; Virginia Commonwealth University; Citadel Military College South Carolina
  摘要：Supersaturated designs investigate more factors than there are runs and are often constructed under a criterion measuring a design's proximity to an unattainable orthogonal design. The most popular analysis identifies active factors by inspecting the solution path of a penalized estimator, such as the lasso. Recent criteria encouraging positive correlations between factors have been shown to produce designs with more definitive solution paths so long as the active factors have positive effects...
• Nicholas T. Longford's contribution to the Discussion of 'Augmented balancing weights as linear regression' by Bruns-Smith et al. AI翻译
  作者：Longford, Nicholas T.
  作者单位：Warsaw School of Economics
• Inference with Mondrian random forests AI翻译
  作者：Cattaneo, Matias Damian; Klusowski, Jason Matthew; Underwood, William George
  作者单位：Princeton University; University of Cambridge
  摘要：Random forests are popular methods for regression and classification analysis, and many different variants have been proposed in recent years. One interesting example is the Mondrian random forest, in which the underlying constituent trees are constructed via a Mondrian process. We give precise bias and variance characterizations, along with a Berry-Esseen-type central limit theorem, for the Mondrian random forest regression estimator. By combining these results with a carefully crafted debias...
• Generalized universal inference on risk minimizers AI翻译
  作者：Dey, Neil; Martin, Ryan; Williams, Jonathan P.
  作者单位：North Carolina State University
  摘要：A common goal in statistics and machine learning is estimation of unknowns. Point estimates alone are of little value without an accompanying measure of uncertainty, but traditional uncertainty quantification methods, such as confidence sets and p-values, often require distributional or structural assumptions that may not be justified in modern applications. The present paper considers a very common case in machine learning, where the quantity of interest is the minimizer of a given risk (expe...
• Empirical likelihood for manifolds AI翻译
  作者：Kurisu, Daisuke; Otsu, Taisuke
  作者单位：University of Tokyo; University of London; London School Economics & Political Science
  摘要：There has been growing interest in statistical analysis of random objects taking values in a non-Euclidean metric space. One important class of such objects consists of data on manifolds. This article is concerned with inference on the Fr & eacute;chet mean and related population objects on manifolds. We develop the concept of nonparametric likelihood for data on manifolds and propose general inference methods by adapting the theory of empirical likelihood. In addition to the basic asymptotic ...
• The partial K function AI翻译
  作者：Grainger, Jake P.; Rajala, Tuomas A.; Murrell, David J.; Olhede, Sofia C.
  作者单位：Natural Resources Institute Finland (Luke); University of London; University College London
  摘要：The K function and its related statistics have been an enduring tool in the analysis of spatial point processes, providing an easy to compute and interpret summary statistic for characterising the interactions between points of one type, or between two different types of points. In this paper, we introduce a partial K function, enabling us to account for some of the effects of the other point types when analysing point-point interactions. The partial K function we introduce reduces to the usua...
• Exact Bayesian inference for Markov switching diffusions AI翻译
  作者：Stumpf-Fetizon, Timothee; Latuszynski, Krzysztof; Palczewski, Jan; Roberts, Gareth
  作者单位：Bocconi University; University of Warwick; Wroclaw University of Science & Technology
  摘要：We develop the first exact Bayesian methodology for the problem of inference in discretely observed regime switching diffusions. Switching diffusion models extend ordinary diffusions by allowing for jumps in instantaneous drift and volatility. The jumps are driven by a latent, continuous-time Markov switching process. We address the problem through an MCMC and an MCEM algorithm that target the exact posterior of diffusion parameters and the latent regime process. The algorithms are exact in th...
• Joshua Cape's contribution to the Discussion of 'Statistical exploration of the Manifold Hypothesis' by Whiteley et al. AI翻译
  作者：Cape, Joshua
  作者单位：University of Wisconsin Madison; University of Wisconsin System; University of Wisconsin Madison
• Robust detection of watermarks for large language models under human edits AI翻译
  作者：Li, Xiang; Ruan, Feng; Wang, Huiyuan; Long, Qi; Su, Weijie J.
  作者单位：University of Pennsylvania; Pennsylvania Medicine; Northwestern University; University of Pennsylvania
  摘要：Watermarking is an effective approach to distinguishing text generated by large language models (LLMs) from human-written text. However, the pervasive presence of human edits on LLM-generated text dilutes watermark signals, thereby significantly degrading detection performance of existing methods. In this paper, by modelling human edits through mixture model detection, we introduce a new method-a truncated goodness-of-fit test (Tr-GoF) for detecting watermarked text under human edits. We prove...