bigSurvSGD: Big Survival Analysis Using Stochastic Gradient Descent

Fits Cox model via stochastic gradient descent. This implementation avoids computational instability of the standard Cox Model when dealing large datasets. Furthermore, it scales up with large datasets that do not fit the memory. It also handles large sparse datasets using proximal stochastic gradient descent algorithm. For more details about the method, please see Aliasghar Tarkhan and Noah Simon (2020) <arXiv:2003.00116v2>.

Getting started

Package details

AuthorAliasghar Tarkhan [aut, cre], Noah Simon [aut]
MaintainerAliasghar Tarkhan <atarkhan@uw.edu>
LicenseGPL (>= 2)
Version0.0.1
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("bigSurvSGD")

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bigSurvSGD documentation built on Oct. 23, 2020, 5:55 p.m.