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Feasible algorithm for linear mixed model for massive data

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Publication:5084778
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DOI10.1080/03610918.2017.1307395OpenAlexW2602255751MaRDI QIDQ5084778

Yanyan Zhao

Publication date: 28 June 2022

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2017.1307395


zbMATH Keywords

linear mixed modelmassive datasequential singular value decomposition


Mathematics Subject Classification ID

Point estimation (62F10)


Related Items

Automatic variable selection in a linear model on massive data



Cites Work

  • Unnamed Item
  • A partially linear framework for massive heterogeneous data
  • Low-rank incremental methods for computing dominant singular subspaces
  • Aggregated estimating equation estimation
  • On the \(QR\) algorithm and updating the \(SVD\) and the \(URV\) decomposition in parallel
  • Sequential Karhunen-Loeve basis extraction and its application to images
  • A split-and-conquer approach for analysis of
  • A Singular Value Decomposition Updating Algorithm for Subspace Tracking
  • Recursive Calculation of Dominant Singular Subspaces
  • Exponential asymptotics of the Mittag–Leffler function
  • A Scalable Bootstrap for Massive Data
  • Extensions and Applications of the Householder Algorithm for Solving Linear Least Squares Problems
  • Linear mixed models for longitudinal data
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