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) tools:::Rd_expr_doi("10.1145/2414416.2414791").
Maintainer: Marc A. Suchard msuchard@ucla.edu
Authors:
Martijn J. Schuemie
Trevor R. Shaddox
Yuxi Tian
Jianxiao Yang
Eric Kawaguchi
Other contributors:
Sushil Mittal [contributor]
Observational Health Data Sciences and Informatics [copyright holder]
Marcus Geelnard (provided the TinyThread library) [copyright holder, contributor]
Rutgers University (provided the HParSearch routine) [copyright holder, contributor]
R Development Core Team (provided the ZeroIn routine) [copyright holder, contributor]
Useful links: