◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Mickael Albertus

4 papers hereh-index 325 citations8 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author3
  • first author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • math.ST4

identity via Semantic Scholar / OpenAlex

activity
20182020
most citedAuxiliary information : the raking-ratio empirical process

5 citations · 7 across the 3 of their papers we have counts for

collaborators

4 papers

math.ST2020★ 1 cited

Exponential increase of the power of the independence and homogeneity chi-square tests with auxiliary information

Mickael Albertus

This paper is an extension of the work about the exponential increase of the power of two non-parametric tests: the Z-test and the chi-square goodness-of-fit test. Subject to h…

math.ST2020★ 1 cited

Asymptotic relatively more efficient test with auxiliary information: the case of the Z-test and the chi-square test

Mickael Albertus

The main goal of this article is to study how an auxiliary information can be used to improve the efficiency of two famous statistical tests: the Z-test and the chi-square test.…

math.ST2019

Raking-ratio empirical process with auxiliary information learning

Mickael Albertus

The raking-ratio method is a statistical and computational method which adjusts the empirical measure to match the true probability of sets of a finite partition. We study the asym…

math.ST2018★ 5 cited

Auxiliary information : the raking-ratio empirical process

Mickael Albertus, Philippe Berthet

We study the empirical measure associated to a sample of size n and modified by N iterations of the raking-ratio method. This empirical measure is adjusted to match the true pr…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.