Computes the random forest variable importance (VIMP) for the conditional inference random forest (cforest) of the 'party' package. Includes a function (varImp) that computes the VIMP for arbitrary measures from the 'measures' package. For calculating the VIMP regarding the measures accuracy and AUC two extra functions exist (varImpACC and varImpAUC).

Estimates the predicted 10-year cardiovascular (CVD) risk score (in probability) for civilian women, women military service 
    members and veterans by inputting patient profiles. The proposed women CVD risk score improves the accuracy of the 
    existing American College of Cardiology/American Heart Association CVD risk assessment
    tool in predicting long‐term CVD risk for VA women, particularly in young and racial/ethnic 
    minority women. See the reference: Jeon‐Slaughter, H., Chen, X., Tsai, S., Ramanan, B., & Ebrahimi, R. 
    (2021) <doi:10.1161/JAHA.120.019217>.

Multi-caller variant analysis pipeline for targeted analysis sequencing (TAS) data. Features a modular, automated workflow that can start with raw reads and produces a user-friendly PDF summary and a spreadsheet containing consensus variant information.

A continuous version of the receiver operating characteristics (ROC) curve to assess both classification and continuity performances of biomarkers, diagnostic tests, or risk prediction models.

A new framework of variable selection, which instead of generating artificial covariates such as permutation importance and knockoffs, creates release rules to examine the affect on the response for each covariate where the conditional distribution of the response variable can be arbitrary and unknown.

In order to make it easy to use variance reduction algorithms for any simulation, this framework can help you.
    We propose user friendly and easy to extend framework. Antithetic Variates, Inner Control Variates,
    Outer Control Variates and Importance Sampling algorithms are available in the framework. User can
    write its own simulation function and use the Variance Reduction techniques in this package to
    obtain more efficient simulations. An implementation of Asian Option simulation is already 
    available within the package. See Kemal Dinçer Dingeç & Wolfgang Hörmann (2012) <doi:10.1016/j.ejor.2012.03.046>.