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) .


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install.packages("bigSurvSGD")

0.0.1 by Aliasghar Tarkhan, 23 days ago


Report a bug at https://github.com/atarkhan/bigSurvSGD/issues


Browse source code at https://github.com/cran/bigSurvSGD


Authors: Aliasghar Tarkhan [aut, cre] , Noah Simon [aut]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports Rcpp, bigmemory, doParallel, survival

Depends on foreach, parallel

Linking to Rcpp


See at CRAN