Zobrazeno 1 - 10
of 379
pro vyhledávání: '"DE IORIO, Maria"'
Understanding the tail behavior of distributions is crucial in statistical theory. For instance, the tail of a distribution plays a ubiquitous role in extreme value statistics, where it is associated with the likelihood of extreme events. There are s
Externí odkaz:
http://arxiv.org/abs/2409.06308
In the era of Big Data, scalable and accurate clustering algorithms for high-dimensional data are essential. We present new Bayesian Distance Clustering (BDC) models and inference algorithms with improved scalability while maintaining the predictive
Externí odkaz:
http://arxiv.org/abs/2408.17153
Over the past two decades, Digital Humanities has transformed the landscape of humanities and social sciences, enabling advanced computational analysis and interpretation of extensive datasets. Notably, recent initiatives in Southeast Asia, particula
Externí odkaz:
http://arxiv.org/abs/2312.13790
Autor:
Cremaschi, Andrea, Yang, Wenjian, De Iorio, Maria, Evans, William E., Yang, Jun J., Rosner, Gary L.
Acute lymphoblastic leukemia (ALL) is a heterogeneous hematologic malignancy involving the abnormal proliferation of immature lymphocytes, accounting for most pediatric cancer cases. ALL management in children has seen great improvement in the last d
Externí odkaz:
http://arxiv.org/abs/2311.04408
High-dimensional data analysis typically focuses on low-dimensional structure, often to aid interpretation and computational efficiency. Graphical models provide a powerful methodology for learning the conditional independence structure in multivaria
Externí odkaz:
http://arxiv.org/abs/2310.11741
Publikováno v:
Biometrics 80 (2024) ujae075
Time-to-event data are often recorded on a discrete scale with multiple, competing risks as potential causes for the event. In this context, application of continuous survival analysis methods with a single risk suffer from biased estimation. Therefo
Externí odkaz:
http://arxiv.org/abs/2308.10583
Standard clustering techniques assume a common configuration for all features in a dataset. However, when dealing with multi-view or longitudinal data, the clusters' number, frequencies, and shapes may need to vary across features to accurately captu
Externí odkaz:
http://arxiv.org/abs/2307.01152
Mixture models are commonly used in applications with heterogeneity and overdispersion in the population, as they allow the identification of subpopulations. In the Bayesian framework, this entails the specification of suitable prior distributions fo
Externí odkaz:
http://arxiv.org/abs/2306.10669
Model calibration, which is concerned with how frequently the model predicts correctly, not only plays a vital part in statistical model design, but also has substantial practical applications, such as optimal decision-making in the real world. Howev
Externí odkaz:
http://arxiv.org/abs/2212.13621
Autor:
Franzolini, Beatrice, Beskos, Alexandros, De Iorio, Maria, Koziell, Warrick Poklewski, Grzeszkiewicz, Karolina
Reliable estimates of volatility and correlation are fundamental in economics and finance for understanding the impact of macroeconomics events on the market and guiding future investments and policies. Dependence across financial returns is likely t
Externí odkaz:
http://arxiv.org/abs/2208.00952