Cyclops v2.0.2


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Cyclic Coordinate Descent for Logistic, Poisson and Survival Analysis

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>.



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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.


  • Regression of very large problems: up to millions of observations, millions of variables
  • Supports (conditional) logistic regression, (conditional) Poisson regression, as well as (conditional) Cox regression
  • Uses a sparse representation of the independent variables when appropriate
  • Supports using no prior, a normal prior or a Laplace prior
  • Supports automatic selection of hyperparameter through cross-validation
  • Efficient estimation of confidence intervals for a single variable using a profile-likelihood for that variable


  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.

System Requirements

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.


User Documentation



Cyclops is licensed under Apache License 2.0. Cyclops contains the TinyThread libray.

The TinyThread library is licensed under the zlib/libpng license as described here.


Cyclops is being developed in R Studio.

Development status



  • This project is supported in part through the National Science Foundation grants IIS 1251151 and DMS 1264153.

Functions in Cyclops

Name Description
fitCyclopsSimulation Fit simulated data
finalizeSqlCyclopsData finalizeSqlCyclopsData
fitCyclopsModel Fit a Cyclops model
getFloatingPointSize Get floating point size
isSorted Check if data are sorted by one or more columns
survfit.cyclopsFit Calculate baseline hazard function
isInitialized Check if a Cyclops data object is initialized
vcov.cyclopsFit Calculate variance-covariance matrix for a fitted Cyclops model object
getCyclopsPredictiveLogLikelihood Compute predictive log-likelihood from a Cyclops model fit
convertToGlmnetLambda Convert to glmnet regularization parameter
getUnivariableCorrelation Get univariable correlation
getUnivariableSeparability Get univariable linear separability
getCovariateTypes Get covariate types
createParameterizedPrior Create a Cyclops parameterized prior object
createPrior Create a Cyclops prior object
cyclops Cyclops: Cyclic coordinate descent for logistic, Poisson and survival analysis
createNonSeparablePrior Create a Cyclops prior object that returns the MLE of non-separable coefficients
getCrossValidationInfo Get cross-validation information from a Cyclops model fit
printCyclopsRowIds Print row identifiers
createControl Create a Cyclops control object
getHyperParameter Get hyperparameter
getNumberOfCovariates Get total number of covariates
mse Mean squared error
createCyclopsData Create a Cyclops data object
getNumberOfRows Get total number of rows
logLik.cyclopsFit Extract log-likelihood
oxford Oxford self-controlled case series data
meanLinearPredictor Calculates xbar*beta
getNumberOfStrata Get number of strata
simulateCyclopsData Simulation Cyclops dataset
printMatrixMarket Print Cyclops data matrix to file
plotCyclopsSimulationFit Plot Cyclops simulation model fit
summary.cyclopsData Cyclops data object summary
getCovariateIds Get covariate identifiers
predict.cyclopsFit Model predictions
readCyclopsData Read Cyclops data from file
reduce Apply simple data reductions
getNumberOfTypes Get total number of outcome types
getSEs Extract standard errors
print.cyclopsData Print a Cyclops data object
print.cyclopsFit Print a Cyclops model fit object
convertToCyclopsVariance Convert to Cyclops Prior Variance
coverage Coverage
createAutoGridCrossValidationControl Create a Cyclops control object that supports multiple hyperparameters
Multitype Create a multitype outcome object
aconfint Asymptotic confidence intervals for a fitted Cyclops model object
coef.cyclopsFit Extract model coefficients
appendSqlCyclopsData appendSqlCyclopsData
confint.cyclopsFit Confidence intervals for Cyclops model parameters
convertToCyclopsData Convert data from two data frames or ffdf objects into a CyclopsData object
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Type Package
License Apache License 2.0
LazyData Yes
LinkingTo Rcpp, BH (>= 1.51.0), RcppEigen (>= 0.3.2)
RoxygenNote 6.1.1
NeedsCompilation yes
Packaged 2019-03-17 14:13:13 UTC; msuchard
Repository CRAN
Date/Publication 2019-03-17 14:53:23 UTC

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