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fastM

R package fastM: Fast Computation of Multivariate M-estimators. The package implements the new algorithm for fast computation of M-scatter matrices using a partial Newton-Raphson procedure for several estimators.

Keywords for this software

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  • R package
  • Gini mean difference
  • spatial rank
  • covariance selection model
  • music performance anxiety
  • empirical sandwich variance estimator
  • arXiv_stat.ME
  • Taylor expansion
  • jstatsoft.org
  • Gaussian graphical models
  • M-estimation
  • partial correlation
  • influence function
  • scatter M-estimator
  • robFitConGraph
  • efficiency
  • R
  • Newton-Raphson algorithm
  • estimating equations
  • M-estimator
  • fixed-point algorithm
  • matrix exponential function
  • affine equivariance
  • arXiv_publication
  • deviance test
  • robust statistics, R
  • arXiv_stat.CO
  • symmetrization

  • URL: cran.r-project.org/web...
  • Code
  • InternetArchive
  • Manual: cran.r-project.org/web...
  • Authors: Lutz Duembgen, Klaus Nordhausen, Heike Schuhmacher
  • Dependencies: R

  • Add information on this software.


  • Related software:
  • R
  • ICSNP
  • ICS
  • robFitConGraph
  • Matrix
  • geeM
  • MASS (R)
  • sandwich
  • gmm
  • geex
  • Show more...
  • saws
  • smoothmest
  • geepack
  • RootSolve
  • mnormt
  • MNM
  • gee
  • ggm
  • CRAN
  • Show less...

References in zbMATH (referenced in 4 articles )

Showing results 1 to 4 of 4.
y Sorted by year (citations)

  1. Daniel Vogel, Stuart J. Watt, Anna Wiedemann: Robustly fitting Gaussian graphical models: the R-package robFitConGraph (2022) arXiv
  2. Bradley C. Saul, Michael G. Hudgens: The Calculus of M-Estimation in R with geex (2020) not zbMATH
  3. Dang, Xin; Sang, Hailin; Weatherall, Lauren: Gini covariance matrix and its affine equivariant version (2019)
  4. Dümbgen, Lutz; Nordhausen, Klaus; Schuhmacher, Heike: New algorithms for (M)-estimation of multivariate scatter and location (2016)

  • Article statistics & filter:

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  • MSC classification / top
    • Top MSC classes
      • 62 Statistics
      • 65 Numerical analysis

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