Large sample theory for merged data from multiple sources

DOI10.1214/18-AOS1727zbMath1418.62256arXiv1805.07800OpenAlexW2962936523WikidataQ128372037 ScholiaQ128372037MaRDI QIDQ2414098

Takumi Saegusa

Publication date: 10 May 2019

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1805.07800

zbMATH Keywords

semiparametric modelcentral limit theoremcalibrationempirical processdata integrationsampling without replacement

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Asymptotic properties of nonparametric inference (62G20) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Central limit and other weak theorems (60F05) Censored data models (62N01)

Related Items (4)

Complex sampling designs: uniform limit theorems and applications ⋮ Improving Trial Generalizability Using Observational Studies ⋮ Nonparametric inference for distribution functions with stratified samples ⋮ Semiparametric inference for merged data from multiple data sources

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