Package: aftsem 1.0

aftsem: Semiparametric Accelerated Failure Time Model

Implements several basic algorithms for estimating regression parameters for semiparametric accelerated failure time (AFT) model. The main methods are: Jin rank-based method (Jin (2003) <doi:10.1093/biomet/90.2.341>), Heller’s estimating method (Heller (2012) <doi:10.1198/016214506000001257>), Polynomial smoothed Gehan function method (Chung (2013) <doi:10.1007/s11222-012-9333-9>), Buckley-James method (Buckley (1979) <doi:10.2307/2335161>) and Jin`s improved least squares method (Jin (2006) <doi:10.1093/biomet/93.1.147>). This package can be used for modeling right-censored data and for comparing different estimation algorithms.

Authors:Martin Benedikt [aut, cre]

aftsem_1.0.tar.gz
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aftsem_1.0.tar.gz(r-4.5-noble)aftsem_1.0.tar.gz(r-4.4-noble)
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aftsem.pdf |aftsem.html✨
aftsem/json (API)

# Install 'aftsem' in R:
install.packages('aftsem', repos = c('https://benedma2.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/benedma2/aftsem-package/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

3.00 score 1 stars 3 scripts 270 downloads 1 exports 13 dependencies

Last updated 1 months agofrom:f03ae9bbbb. Checks:OK: 2 NOTE: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 17 2024
R-4.5-win-x86_64NOTEOct 17 2024
R-4.5-linux-x86_64OKOct 17 2024
R-4.4-win-x86_64NOTEOct 17 2024
R-4.4-mac-x86_64NOTEOct 17 2024
R-4.4-mac-aarch64NOTEOct 17 2024
R-4.3-win-x86_64NOTEOct 17 2024
R-4.3-mac-x86_64NOTEOct 17 2024
R-4.3-mac-aarch64NOTEOct 17 2024

Exports:aftsem

Dependencies:latticeMASSMatrixMatrixModelsnloptrnumDerivoptimxpracmaquantregRcppRcppArmadilloSparseMsurvival