This model fitting tool incorporates cyclic coordinate descent and
majorization-minimization approaches to fit a variety of regression models
found in large-scale observational healthcare data. Implementations focus
on computational optimization and fine-scale parallelization to yield
efficient inference in massive datasets. Please see:
Suchard, Simpson, Zorych, Ryan and Madigan (2013)
|Author||Marc A. Suchard [aut, cre], Martijn J. Schuemie [aut], Trevor R. Shaddox [aut], Yuxi Tian [aut], Sushil Mittal [ctb], Observational Health Data Sciences and Informatics [cph], Marcus Geelnard [cph, ctb] (provided the TinyThread library), Rutgers University [cph, ctb] (provided the HParSearch routine), R Development Core Team [cph, ctb] (provided the ZeroIn routine)|
|Date of publication||2018-06-15 15:50:20 UTC|
|Maintainer||Marc A. Suchard <[email protected]>|
|License||Apache License 2.0|
|Package repository||View on CRAN|
Install the latest version of this package by entering the following in R:
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.