2024

最新文章

• Graphical criteria for the identification of marginal causal effects in continuous-time survival and event-history analyses AI翻译
  作者：Roysland, Kjetil; Ryalen, Pal C.; Nygard, Mari; Didelez, Vanessa
  作者单位：University of Oslo; Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne; University of Oslo; Norwegian Institute of Public Health (NIPH); University of Bremen; Leibniz Association; Leibniz Institute for Prevention Research & Epidemiology (BIPS)
  摘要：We consider continuous-time survival and event-history settings, where our aim is to graphically represent causal structures allowing us to characterize when a causal parameter is identified from observational data. This causal parameter is formalized as the effect on an outcome event of a (possibly hypothetical) intervention on the intensity of a treatment process. To establish identifiability, we propose novel graphical rules indicating whether the observed information is sufficient to obtai...
• Glenn Shafer's contribution to the Discussion of 'Safe testing' by Grünwald, de Heide, and Koolen AI翻译
  作者：Shafer, Glenn
  作者单位：Rutgers University System; Rutgers University Newark; Rutgers University New Brunswick
• Vladimir Vovk's contribution to the Discussion of 'Safe testing' by Grunwald, de Heide, and Koolen AI翻译
  作者：Vovk, Vladimir
  作者单位：University of London; Royal Holloway University London
• Filippo Ascolani, Antonio Lijoi and Igor Prünster's contribution to the Discussion of 'Root and community inference on the latent growth process of a network' by Crane and Xu AI翻译
  作者：Ascolani, Filippo; Lijoi, Antonio; Pruenster, Igor
  作者单位：Duke University; Bocconi University
• Nonparametric measure-transportation-based methods for directional data AI翻译
  作者：Hallin, M.; Liu, H.; Verdebout, T.
  作者单位：Universite Libre de Bruxelles; Universite Libre de Bruxelles; Chinese Academy of Sciences; University of Science & Technology of China, CAS
  摘要：This article proposes various nonparametric tools based on measure transportation for directional data. We use optimal transports to define new notions of distribution and quantile functions on the hypersphere, with meaningful quantile contours and regions and closed-form formulas under the classical assumption of rotational symmetry. The empirical versions of our distribution functions enjoy the expected Glivenko-Cantelli property of traditional distribution functions. They provide fully dist...
• Authors' reply to the Discussion of 'From denoising diffusions to denoising Markov models' at the Discussion Meeting on 'Probabilistic and statistical aspects of machine learning' AI翻译
  作者：Benton, Joe; Shi, Yuyang; De Bortoli, Valentin; Deligiannidis, George; Doucet, Arnaud
  作者单位：University of Oxford; Universite PSL; Ecole Normale Superieure (ENS)
• Ayla Jungbluth and Johannes Lederer's contribution to the Discussion of 'the Discussion Meeting on Probabilistic and statistical aspects of machine learning' AI翻译
  作者：Jungbluth, Ayla; Lederer, Johannes
  作者单位：Ruhr University Bochum
• Hernando Ombao's contribution to the Discussion of 'the Discussion Meeting on Probabilistic and statistical aspects of machine learning' AI翻译
  作者：Li, Jie; Fearnhead, Paul; Fryzlewicz, Piotr; Wang, Tengyao
  作者单位：University of London; London School Economics & Political Science; Lancaster University
  摘要：Detecting change points in data is challenging because of the range of possible types of change and types of behaviour of data when there is no change. Statistically efficient methods for detecting a change will depend on both of these features, and it can be difficult for a practitioner to develop an appropriate detection method for their application of interest. We show how to automatically generate new offline detection methods based on training a neural network. Our approach is motivated b...
• Testing high-dimensional multinomials with applications to text analysis AI翻译
  作者：Cai, T. Tony; Ke, Zheng T.; Turner, Paxton
  作者单位：University of Pennsylvania; Harvard University
  摘要：Motivated by applications in text mining and discrete distribution inference, we test for equality of probability mass functions of K groups of high-dimensional multinomial distributions. Special cases of this problem include global testing for topic models, two-sample testing in authorship attribution, and closeness testing for discrete distributions. A test statistic, which is shown to have an asymptotic standard normal distribution under the null hypothesis, is proposed. This parameter-free...
• Torben Martinussen's contribution to the Discussion of 'Parameterizing and simulating from causal models' by Evans and Didelez AI翻译
  作者：Martinussen, Torben
  作者单位：University of Copenhagen