3 papers
stat.ME2026
Relative Wasserstein Spatial Depth for Cluster Number Selection in Distributional Data
Chenqin Xu, Yisha Yao
Contemporary data in many scientific domains, such as images, media streams, biomedical omics, are naturally modeled as probability distributions in Wasserstein space instead of po…
math.ST2025
Nonparametric Vector Quantile Autoregression
Alberto González-Sanz, Marc Hallin, Yisha Yao
Prediction is a key issue in time series analysis. Just as classical mean regression models, classical autoregressive methods, yielding L point-predictions, provide rather poor…
math.ST2024
Wasserstein Spatial Depth
François Bachoc, Alberto González-Sanz, Jean-Michel Loubes +1
Modeling observations as random distributions embedded within Wasserstein spaces is becoming increasingly popular across scientific fields, as it captures the variability and geome…