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) <doi:10.1145/2414416.2414791>.
|Author||Marc A. Suchard [aut, cre], Martijn J. Schuemie [aut], Trevor R. Shaddox [aut], Yuxi Tian [aut], Jianxiao Yang [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)|
|Maintainer||Marc A. Suchard <firstname.lastname@example.org>|
|License||Apache License 2.0|
|Package repository||View on CRAN|
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