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Cyclops

Cyclops is part of the OHDSI Methods Library.

Introduction

Cyclops (Cyclic coordinate descent for logistic, Poisson and survival analysis) is an R package for performing large scale regularized regressions.

Features

  • 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

Examples

  library(Cyclops)
  cyclopsData <- createCyclopsDataFrame(formula)
  cyclopsFit <- fitCyclopsModel(cyclopsData)

Technology

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.

Installation

In R, to install the latest stable version, install from CRAN:

install.packages("Cyclops")

To install the latest development version, install from GitHub. Note that this will require RTools to be installed.

install.packages("devtools")
devtools::install_github("ohdsi/Cyclops")

User Documentation

Support

  • Developer questions/comments/feedback: OHDSI Forum
  • We use the GitHub issue tracker for all bugs/issues/enhancements

License

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.

Development

Cyclops is being developed in R Studio.

Development status

Beta

Acknowledgements

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

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Version

Install

install.packages('Cyclops')

Monthly Downloads

1,719

Version

2.0.2

License

Apache License 2.0

Issues

Pull Requests

Stars

Forks

Maintainer

Marc A Suchard

Last Published

March 17th, 2019

Functions in Cyclops (2.0.2)

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