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
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). Installation on Windows requires RTools (devtools >= 1.12 required for RTools34, otherwise RTools33 works fine).
- There are no dependencies.
- On Windows, make sure RTools is installed.
- In R, use the following commands to download and install Cyclops:
install.packages("devtools")
library(devtools)
install_github("ohdsi/Cyclops") - To perform a Cyclops model fit, use the following commands in R:
library(Cyclops)
cyclopsData <- createCyclopsDataFrame(formula)
cyclopsFit <- fitCyclopsModel(cyclopsData)- Package manual: Cyclops manual
- Developer questions/comments/feedback: OHDSI Forum
- We use the GitHub issue tracker for all bugs/issues/enhancements
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
Beta
- This project is supported in part through the National Science Foundation grants IIS 1251151 and DMS 1264153.