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). Compilation on Windows requires RTools >= 3.4.

- There are no dependencies.

- On Windows, make sure RTools is installed.
- In R, use the following commands to download and install Cyclops:

`r install.packages("devtools") library(devtools) install_github("ohdsi/Cyclops")`

- To perform a Cyclops model fit, use the following commands in R:

`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.

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