The R Journal: article published in 2013, volume 5:1

Fast Pure R Implementation of GEE: Application of the Matrix Package
Lee S. McDaniel, Nicholas C. Henderson and Paul J. Rathouz , The R Journal (2013) 5:1, pages 181-187.

Abstract Generalized estimating equation solvers in R only allow for a few pre-determined options for the link and variance functions. We provide a package, geeM, which is implemented entirely in R and allows for user specified link and variance functions. The sparse matrix representations provided in the Matrix package enable a fast implementation. To gain speed, we make use of analytic inverses of the working correlation when possible and a trick to find quick numeric inverses when an analytic inverse is not available. Through three examples, we demonstrate the speed of geeM, which is not much worse than C implementations like geepack and gee on small data sets and faster on large data sets.

Received: 2012-10-17; online 2013-06-03
CRAN packages: geepack, gee, geeM, Matrix , CRAN Task Views implied by cited CRAN packages: Econometrics, SocialSciences, Multivariate, NumericalMathematics


CC BY 4.0
This article is licensed under a Creative Commons Attribution 3.0 Unported license .

@article{RJ-2013-017,
  author = {Lee S. McDaniel and Nicholas C. Henderson and Paul J.
          Rathouz},
  title = {{Fast Pure R Implementation of GEE: Application of the Matrix
          Package}},
  year = {2013},
  journal = {{The R Journal}},
  url = {https://journal.r-project.org/archive/2013/RJ-2013-017/index.html},
  pages = {181--187},
  volume = {5},
  number = {1}
}