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)
Cyclops is part of the OHDSI Methods Library.
Cyclops (Cyclic coordinate descent for logistic, Poisson and survival analysis) is an R package for performing large scale regularized regressions.
library(Cyclops)cyclopsData <- createCyclopsDataFrame(formula)cyclopsFit <- fitCyclopsModel(cyclopsData)
Cyclops in an R package, with most functionality implemented in C++. Cyclops uses cyclic coordinate descent to optimize the likelihood function, which makes use of the sparse nature of the data.
Requires R (version 3.1.0 or higher). Compilation on Windows requires RTools >= 3.4.
In R, to install the latest stable version, install from CRAN:
To install the latest development version, install from GitHub. Note that this will require RTools to be installed.
Cyclops is licensed under Apache License 2.0. Cyclops contains the TinyThread libray.
Cyclops is being developed in R Studio.
RNGversion("3.5.0")in unit-tests to reproduce old RNG behavior
RcppParallel(until TBB is again R-compliant)
<complex>header, needed for
pragmastatements used to quiet
.checkCovariateswhen excluding covariates from regularization
ff.data.framewith size == 0
Changes: initial submission to CRAN