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researcher

Arthur Charpentier

23 papers hereh-index 10568 citations39 works total

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

author position
  • sole author4
  • first author8
  • middle author3
  • last author7

Across the 22 of 23 papers where every author was matched, so the position is known.

fields
  • stat.ML6
  • econ.EM4
  • stat.AP4
  • econ.GN2
  • q-bio.PE2
  • q-fin.RM2
same name
  • Arthur Charpentier — 17 papers, h 4
  • Arthur Charpentier — 11 papers, h 21
  • Arthur Charpentier — 7 papers, h 3
  • Arthur Charpentier — 3 papers, h 2
  • Arthur Charpentier — 1 paper, h 0
  • Arthur Charpentier — 1 paper, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20192026
most citedPredicting Drought and Subsidence Risks in France

30 citations · 74 across the 20 of their papers we have counts for

collaborators
Showing 2021Show all

4 papers · 1 filter

econ.EM2021

Weighted asymmetric least squares regression with fixed-effects

Amadou Barry, Karim Oualkacha, Arthur Charpentier

The fixed-effects model estimates the regressor effects on the mean of the response, which is inadequate to summarize the variable relationships in the presence of heteroscedastici…

stat.AP2021★ 30 cited

Predicting Drought and Subsidence Risks in France

Arthur Charpentier, Molly James, Hani Ali

The economic consequences of drought episodes are increasingly important, although they are often difficult to apprehend in part because of the complexity of the underlying mechani…

q-fin.RM2021★ 3 cited

Collaborative Insurance Sustainability and Network Structure

Arthur Charpentier, Lariosse Kouakou, Matthias Löwe +2

The peer-to-peer (P2P) economy has been growing with the advent of the Internet, with well known brands such as Uber or Airbnb being examples thereof. In the insurance sector the a…

stat.ML2021

Autocalibration and Tweedie-dominance for Insurance Pricing with Machine Learning

Michel Denuit, Arthur Charpentier, Julien Trufin

Boosting techniques and neural networks are particularly effective machine learning methods for insurance pricing. Often in practice, there are nevertheless endless debates about t…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.