Title: Fine-Gray Regression via Forward-Backward Scan
Maintainer: Eric S. Kawaguchi <ekawaguc@usc.edu>
Description: In competing risks regression, the proportional subdistribution hazards (PSH) model is popular for its direct assessment of covariate effects on the cumulative incidence function. This package allows for both penalized and unpenalized PSH regression in linear time using a novel forward-backward scan. Penalties include Ridge, Lease Absolute Shrinkage and Selection Operator (LASSO), Smoothly Clipped Absolute Deviation (SCAD), Minimax Concave Plus (MCP), and elastic net.
Packaged: 2019-09-05 14:38:03 UTC; erickawaguchi

Packaged: 2019-09-10 21:26:19 UTC; erickawaguchi

Title: Lasso and elastic-net penalized Cox's regression in high
dimensions models using the cocktail algorithm
Author: Yi Yang <yiyang@umn.edu>, Hui Zou <hzou@stat.umn.edu>
Description: We implement a cocktail algorithm, a good mixture of
coordinate decent, the majorization-minimization principle and
the strong rule, for computing the solution paths of the
elastic net penalized Cox's proportional hazards model.

Description: We implement a cocktail algorithm, a good mixture of coordinate decent, the majorization-minimization principle and the strong rule, for computing the solution paths of the elastic net penalized Cox's proportional hazards model.

Title: Lasso and Elastic-Net Penalized Cox's Regression in High
Dimensions Models using the Cocktail Algorithm
Author: Yi Yang <yi.yang6@mcgill.ca>, Hui Zou <hzou@stat.umn.edu>
Description: We implement a cocktail algorithm, a good mixture of coordinate decent, the majorization-minimization principle and the strong rule, for computing the solution paths of the elastic net penalized Cox's proportional hazards model. The package is an implementation of Yang, Y. and Zou, H. (2013) DOI: <doi:10.4310/SII.2013.v6.n2.a1>.

Title: Fast, Low Memory-Footprint Digests of R Objects
Description: Provides an R interface to Bob Jenkin's streaming,
non-cryptographic 'SpookyHash' hash algorithm for use in digest-based
comparisons of R objects. 'fastdigest' plugs directly into R's internal
serialization machinery, allowing digests of all R objects the serialize()
function supports, including reference-style objects via custom hooks. Speed is
high and scales linearly by object size; memory usage is constant and
Author: Gabriel Becker, Bob Jenkins (SpookyHash algorithm and C++ implementation)