plsRcox: Partial Least Squares Regression for Cox Models and Related
Techniques
Provides Partial least squares Regression and various regular, sparse or kernel, techniques for fitting Cox models in high dimensional settings <doi:10.1093/bioinformatics/btu660>, Bastien, P., Bertrand, F., Meyer N., Maumy-Bertrand, M. (2015), Deviance residuals-based sparse PLS and sparse kernel PLS regression for censored data, Bioinformatics, 31(3):397-404. Cross validation criteria were studied in <arXiv:1810.02962>, Bertrand, F., Bastien, Ph. and Maumy-Bertrand, M. (2018), Cross validating extensions of kernel, sparse or regular partial least squares regression models to censored data.
Version: |
1.7.6 |
Depends: |
R (≥ 2.4.0) |
Imports: |
survival, plsRglm, lars, pls, kernlab, mixOmics, risksetROC, survcomp, survAUC, rms |
Suggests: |
survivalROC, plsdof |
Published: |
2021-03-19 |
Author: |
Frederic Bertrand
[cre, aut],
Myriam Maumy-Bertrand
[aut] |
Maintainer: |
Frederic Bertrand <frederic.bertrand at math.unistra.fr> |
BugReports: |
https://github.com/fbertran/plsRcox/issues/ |
License: |
GPL-3 |
URL: |
http://fbertran.github.io/plsRcox/,
https://github.com/fbertran/plsRcox/ |
NeedsCompilation: |
no |
Classification/MSC: |
62N01, 62N02, 62N03, 62N99 |
Citation: |
plsRcox citation info |
Materials: |
README |
In views: |
Survival |
CRAN checks: |
plsRcox results |
Documentation:
Downloads:
Reverse dependencies:
Linking:
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