Package: bigSurvSGD 1.0.0

bigSurvSGD: Big Survival Analysis Using Stochastic Gradient Descent

Fits Cox Model via stochastic gradient descent (SGD). 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.

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

bigSurvSGD_1.0.0.tar.gz
bigSurvSGD_1.0.0.zip(r-4.5)bigSurvSGD_1.0.0.zip(r-4.4)bigSurvSGD_1.0.0.zip(r-4.3)
bigSurvSGD_1.0.0.tgz(r-4.5-x86_64)bigSurvSGD_1.0.0.tgz(r-4.5-arm64)bigSurvSGD_1.0.0.tgz(r-4.4-x86_64)bigSurvSGD_1.0.0.tgz(r-4.4-arm64)bigSurvSGD_1.0.0.tgz(r-4.3-x86_64)bigSurvSGD_1.0.0.tgz(r-4.3-arm64)
bigSurvSGD_1.0.0.tar.gz(r-4.5-noble)bigSurvSGD_1.0.0.tar.gz(r-4.4-noble)
bigSurvSGD_1.0.0.tgz(r-4.4-emscripten)bigSurvSGD_1.0.0.tgz(r-4.3-emscripten)
bigSurvSGD.pdf |bigSurvSGD.html
bigSurvSGD/json (API)

# Install 'bigSurvSGD' in R:
install.packages('bigSurvSGD', repos = c('https://atarkhan.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/atarkhan/bigsurvsgd/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

cpp

2.85 score 7 stars 1 scripts 219 downloads 6 exports 12 dependencies

Last updated 5 years agofrom:8dc4e4aa4b. Checks:1 OK, 11 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 06 2025
R-4.5-win-x86_64NOTEMar 06 2025
R-4.5-mac-x86_64NOTEMar 06 2025
R-4.5-mac-aarch64NOTEMar 06 2025
R-4.5-linux-x86_64NOTEMar 06 2025
R-4.4-win-x86_64NOTEMar 06 2025
R-4.4-mac-x86_64NOTEMar 06 2025
R-4.4-mac-aarch64NOTEMar 06 2025
R-4.4-linux-x86_64NOTEMar 06 2025
R-4.3-win-x86_64NOTEMar 06 2025
R-4.3-mac-x86_64NOTEMar 06 2025
R-4.3-mac-aarch64NOTEMar 06 2025

Exports:bigSurvSGDlambdaMaxConeChunkConeObsPlugingCplot.bigSurvSGDprint.bigSurvSGD

Dependencies:BHbigmemorybigmemory.sricodetoolsdoParallelforeachiteratorslatticeMatrixRcppsurvivaluuid