Stein discrepancy 2distributional models 1extreme value theory 1geometric regularisation 1godambe information 1graphical models 1identifiability 1information geometry 1markov chains 1order statistics 1record values 1stochastic processes 1
From the 3 of 3 linked papers with an AI index.
3 papers
math.PR2026
Markov Properties of -Record Processes via Order Statistics
Rodrigo Labouriau
The paper derives a direct probabilistic construction of k‑record processes by showing that the sequence of k‑th largest observations forms a Markov chain, and uses this framework…
math.ST2026
Weak Information Geometry: Riemannian Structures from Distributional Inference Functions and Stein Discrepancies
Rodrigo Labouriau
The paper extends information geometry beyond the classical Fisher‑Rao framework by using tempered distributions and weak inference instruments to define Godambe metrics on paramet…
math.ST2026
Transversality and Geometric Regularisation in Distributional Statistical Models
R. Labouriau
The paper develops a statistical framework that replaces classical densities with tempered distribution‑kernel pairs, showing that the smoothing kernel acts as a geometric regulari…