carSurv-package: Correlation-Adjusted Regression Survival Scores

In carSurv: Correlation-Adjusted Regression Survival (CARS) Scores

Description

Contains functions to estimate the Correlation-Adjusted Regression Survival (CARS) Scores. The main function is carSurvScore, which estimates CARS scores of each variable. The higher the absolute values of CARS scores, the higher the variable importance. Additionally there is the function carVarSelect to select cut-off thresholds to separate variables associated with survival from noise variables. There are two possible cut-off threshold options: False non-discovery rate q-values and empirical quantiles of the raw scores.

Details

Package: carSurv

Type: Package

Version: 1.0.0

Date: 2018-02-24

License: GPL-3

Author(s)

Thomas Welchowski (Maintainer) [e-mail]

References

Welchowski, T. and Zuber, V. and Schmid, M., (2018), Correlation-Adjusted Regression Survival Scores for High-Dimensional Variable Selection, <arXiv:1802.08178>

Zuber, V. and Strimmer, K., (2011), High-Dimensional Regression and Variable Selection Using CAR Scores, Statistical Applications in Genetics and Molecular Biology

Schaefer, J. and Strimmer, K., (2005), A Shrinkage Approach to Large-Scale Covariance Matrix Estimation and Implications for Functional Genomics, Statistical Applications in Genetics and Molecular Biology

Van der Laan, M. J. and Robins, J. M., (2003), Unified Methods for Censored Longitudinal Data and Causality, Springer Series in Statistics Strimmer, K., (2008), A unified approach to false discovery rate estimation, BMC Bioinformatics

carSurv documentation built on May 1, 2019, 8:44 p.m.