Overview
This class aims to introduce the main theoretical foundations of asymptotic statistics.
Asymptotic Statistics M2RI (Toulouse University, 2025-2026)
Lecturers: Clément Lalanne, Pierre Neuvial for the other part of the classEvaluation
For all students, the final grade will consist of an 100% weight from the exam.Lectures
- Lecture 1 Introduction and Random Vectors 1 (notes).
- Lecture 2 Random Vectors 1 continued and Random Vectors 2 (notes)
- Lecture 3
- Lecture 4
- Lecture 5
- Lecture 6
- Lecture 7
References and External Resources
Old page for the class by François Bachoc.Statistics
- Asymptotic Statistics by A. W. van der Vaart, 2000.
Measure and Probability Theory
- Intégration, Probabilités et Processus Aléatoires by Jean-François Le Gall, 2006: An excellent introduction to measure theory with elements of stochastic processes and conditional expectation.
- Probabilités 2 by Jean-Yves Ouvrard, 2009: A detailed treatment of advanced topics in probability theory.
- Exercices de probabilités by M. Cottrell, C. Duhamel, V. Genon-catalot, T. Meyre, 2016.
- Concentration Inequalities: A Nonasymptotic Theory of Independence by Stéphane Boucheron, Gábor Lugosi, and Pascal Massart, 2013.
Machine Learning and Learning Theory
Analysis
- Cours d'analyse by Jean-Michel Bony, 2001.