Divide and recombine (D&R): Data science for large complex data

DOI10.1002/sam.11242OpenAlexW1999036265MaRDI QIDQ4969983

William S. Cleveland, Ryan Hafen

Publication date: 14 October 2020

Published in: Statistical Analysis and Data Mining: The ASA Data Science Journal (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/sam.11242

Mathematics Subject Classification ID

Statistics (62-XX) Computer science (68-XX)

Related Items (4)

A model robust subsampling approach for generalised linear models in big data settings ⋮ Communication-Efficient Distributed Statistical Inference ⋮ Divide and recombine (D{\&}R) data science projects for deep analysis of big data and high computational complexity ⋮ Predictive models for trajectory risks prediction from repeated ordinal outcomes

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