papers

Publications (7)

math.HO2026

From Coefficients to Distributions: De~Moivre and the Operational View of Probability

R. Labouriau

We trace a conceptual genealogy from Abraham de Moivre's derivation of the normal curve (1733) to the modern distributional approach to statistics. De Moivre's Approximatio ad Summ…

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…

#distributional models#geometric regularisation#transversality#identifiability
math.PR2026

Distributional Statistical Models: Weak Moments, Cumulants, and a Central Limit Theorem

R. Labouriau

Many important statistical models fall outside classical moment-based methods due to the non-existence of moments or moment generating functions. We propose a generalised probabili…

math.HO2026

Notes on Transversality and Statistical Degeneracies in Distributional Models

R. Labouriau

These notes provide a pedagogical introduction to the role of transversality theory in the analysis of statistical degeneracies within the framework of distributional statistical m…

stat.ME2026

Weak Moment Methods for Statistical Inference: with an Application to Robust Estimation

R. Labouriau

A companion paper develops a generalised framework in which a probability law is represented by a tempered distribution - on the same footing as a density or cha…

math.ST2026

Inference Functionals and Observation Operators for Distributional Statistical Models

R. Labouriau

This paper generalises inference functions (Godambe, 1960) to distributional statistical models, in which each probability measure is represented by a distribution--kernel pair $(T…