An API for M-Estimation

Provides a general, flexible framework for estimating parameters and empirical sandwich variance estimator from a set of unbiased estimating equations (i.e., M-estimation in the vein of Stefanski & Boos (2002) ). Also provides an API to compute finite-sample variance corrections.


geex 1.0.3

  • adds basic examples for most functions, though to be sure, the vignettes provide more useful examples.

geex 1.0.2

  • requires R >= 3.3

geex 1.0.1

  • add a call slot to the S4 geex object. Now the update function can be used to update elements of an m_estimate call.

geex 1.0.0

  • implements an S4 system throughout geex
  • estimate_equations becomes m_estimate. See documentation for changes to arguments. Notably, eeFUN becomes estFUN
  • make_eeFUN functions become grab_psiFUN
  • speeds up the summation of list of matrices with compute_sum_of_list
  • plus many more updates and vignettes

geex 0.3.0

  • adds a weights argument to estimate_equations for faster computations with grouped data. See the weights vignette for a demonstration.

geex 0.2.2

  • changes names of list items used in a corrections_list in estimate_equations. Each item of the correction_list must itself be a list at least one item: correctFUN. Additional arguments to correctFUN may be passed via correctFUN_control.

geex 0.2.1

  • adds a vignette explaining how to use a different root finding algorithm via rootFUN argument in estimate_equations
  • fixes issues where different rootFUNs would not work:
    • roots argument no longer needs to be set if compute_roots = TRUE. Instead, starting values are passed via the rootFUN_control list.
    • Removes the start argument from compute_eeroots; set this option in rootFUN_control.

geex 0.2.0

  • overhauls which arguments are passed to estimate_equations and how these arguments are parsed internally. See this function's documentation for details
  • adds geexex dataset for use in examples

geex 0.1.0

  • the inital geex release

Reference manual

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1.0.3 by Bradley Saul, 6 months ago,

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Browse source code at

Authors: Bradley Saul [aut, cre], Brian Barkley [ctb]

Documentation:   PDF Manual  

MIT + file LICENSE license

Imports Matrix, rootSolve, numDeriv, lme4, methods

Suggests testthat, knitr, dplyr, moments, sandwich, inferference, xtable, AER, ICSNP, MASS, gee, ivpack, saws, rmarkdown, geepack, covr

See at CRAN