SuperSurv

R 패키지 메타데이터와 수집 신호를 모아 봅니다.

Packages / CRAN / SuperSurv

SuperSurv

v0.1.7

SuperSurv

Repository CRANLicense MIT + file LICENSELifecycle activeNeeds compilation no

Package page Reference Source DOI README

DOI

10.32614/CRAN.package.SuperSurv

Core Signals

첫 화면에서 판단해야 할 수집 신호를 먼저 배치합니다.

표시할 핵심 신호가 없습니다.

Supported Backends

DESCRIPTION에서 감지한 backend 관련 package입니다.

backend package 신호가 없습니다.

Quick Facts

기본 메타데이터를 작은 카드와 토큰으로 압축합니다.

profile

Repository

CRAN

Version

0.1.7

License

MIT + file LICENSE

Lifecycle

active

Needs compilation

Last observed

2026-06-23

CRAN: cran.r-project.org/package=SuperSurv

수집 소스별 패키지 정보

1개 소스

CRAN

0.1.7

2026-06-23

License

MIT + file LICENSE

Depends

R (>= 4.0.0)

Imports

survival, nnls, future.apply, stats, utils, dplyr, magrittr

Suggests

aorsf, BART, CoxBoost, glmnet, gbm, mgcv, randomForestSRC, ranger, rpart, survivalsvm, xgboost, survex, ggplot2, tidyr, quadprog, ggforce, patchwork, knitr, rmarkdown

Needs compilation

Lifecycle

active

Last observed

2026-06-23 19:50:20

이 패키지가 의존하는 패키지

5개 표시전체 27개

Package	Type	Spec
dplyr CRAN · 0.1.7 · 2026-06-23	Imports	dplyr
future.apply CRAN · 0.1.7 · 2026-06-23	Imports	future.apply
magrittr CRAN · 0.1.7 · 2026-06-23	Imports	magrittr
nnls CRAN · 0.1.7 · 2026-06-23	Imports	nnls
stats CRAN · 0.1.7 · 2026-06-23	Imports	stats
survival CRAN · 0.1.7 · 2026-06-23	Imports	survival
utils CRAN · 0.1.7 · 2026-06-23	Imports	utils
aorsf CRAN · 0.1.7 · 2026-06-23	Suggests	aorsf
BART CRAN · 0.1.7 · 2026-06-23	Suggests	BART
CoxBoost CRAN · 0.1.7 · 2026-06-23	Suggests	CoxBoost
fastshap CRAN · 0.1.2 · 2026-06-10	Suggests	fastshap
gbm CRAN · 0.1.7 · 2026-06-23	Suggests	gbm
ggforce CRAN · 0.1.7 · 2026-06-23	Suggests	ggforce
ggplot2 CRAN · 0.1.7 · 2026-06-23	Suggests	ggplot2
glmnet CRAN · 0.1.7 · 2026-06-23	Suggests	glmnet
knitr CRAN · 0.1.7 · 2026-06-23	Suggests	knitr
mgcv CRAN · 0.1.7 · 2026-06-23	Suggests	mgcv
patchwork CRAN · 0.1.7 · 2026-06-23	Suggests	patchwork
quadprog CRAN · 0.1.7 · 2026-06-23	Suggests	quadprog
randomForestSRC CRAN · 0.1.7 · 2026-06-23	Suggests	randomForestSRC
ranger CRAN · 0.1.7 · 2026-06-23	Suggests	ranger
rmarkdown CRAN · 0.1.7 · 2026-06-23	Suggests	rmarkdown
rpart CRAN · 0.1.7 · 2026-06-23	Suggests	rpart
survex CRAN · 0.1.7 · 2026-06-23	Suggests	survex
survivalsvm CRAN · 0.1.7 · 2026-06-23	Suggests	survivalsvm
tidyr CRAN · 0.1.7 · 2026-06-23	Suggests	tidyr
xgboost CRAN · 0.1.7 · 2026-06-23	Suggests	xgboost
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1 / 6

이 패키지를 쓰는 패키지

0개 표시전체 0개

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패키지 페이지

All links

Repository: CRAN
Version: 0.1.2
Collected: 2026-06-04 08:16:45
Package page: https://cran.r-project.org/web/packages/SuperSurv/index.html
DOI: 10.32614/CRAN.package.SuperSurv
Citation: https://cran.r-project.org/web/packages/SuperSurv/citation.html
CRAN checks: https://cran.r-project.org/web/checks/check_results_SuperSurv.html
README: https://cran.r-project.org/web/packages/SuperSurv/readme/README.html
Reference HTML: https://cran.r-project.org/web/packages/SuperSurv/refman/SuperSurv.html
Reference PDF: https://cran.r-project.org/web/packages/SuperSurv/SuperSurv.pdf
Source package: https://cran.r-project.org/src/contrib/SuperSurv_0.1.2.tar.gz
Archive: https://CRAN.R-project.org/src/contrib/Archive/SuperSurv

Page fields

Author: Yue Lyu [aut, cre]
BugReports: https://github.com/yuelyu21/SuperSurv/issues
CRAN Checks: SuperSurv results [issues need fixing before 2026-06-10]
Citation: SuperSurv citation info
DOI: 10.32614/CRAN.package.SuperSurv
License: MIT + file LICENSE
Maintainer: Yue Lyu <yuelyu0521 at gmail.com>
Materials: README
NeedsCompilation: no
Old Sources: SuperSurv archive
Package Source: SuperSurv_0.1.2.tar.gz
Published: 2026-05-04
Reference Manual: SuperSurv.html , SuperSurv.pdf
URL: https://github.com/yuelyu21/SuperSurv , https://yuelyu21.github.io/SuperSurv/
Version: 0.1.2
Vignettes: 06. Machine Learning with Random Survival Forests ( source , R code ) 09. Causal Effects and Adjusted Marginal Contrasts (RMST) ( source , R code ) 11. Extending SuperSurv ( source , R code ) 05. Advanced Hyperparameter Tuning & Grid Search ( source , R code ) 00. Installation & Setup ( source , R code ) 02. Model Performance & Benchmarking ( source , R code ) 07. Parametric Survival Models ( source , R code ) 10. Scaling Up with Parallel Processing ( source , R code ) 04. High-Dimensional Data & Variable Screening ( source , R code ) 08. Interpreting the Black Box with SHAP & survex ( source , R code ) 03. Ensemble vs. Best Model Selection ( source , R code ) 01. SuperSurv with Ensemble ( source , R code )
Windows Binaries: r-devel: SuperSurv_0.1.2.zip , r-release: SuperSurv_0.1.2.zip , r-oldrel: SuperSurv_0.1.2.zip
MacOS Binaries: r-release (arm64): SuperSurv_0.1.2.tgz , r-oldrel (arm64): SuperSurv_0.1.2.tgz , r-release (x86_64): SuperSurv_0.1.2.tgz , r-oldrel (x86_64): SuperSurv_0.1.2.tgz

Version

0.1.2

Published

2026-05-04

DOI

10.32614/CRAN.package.SuperSurv

Author

Yue Lyu [aut, cre]

Maintainer

Yue Lyu <yuelyu0521 at gmail.com>

BugReports

https://github.com/yuelyu21/SuperSurv/issues

License

MIT + file LICENSE

MIT LICENSE

URL

https://github.com/yuelyu21/SuperSurv , https://yuelyu21.github.io/SuperSurv/

https://github.com/yuelyu21/SuperSurv https://yuelyu21.github.io/SuperSurv/

NeedsCompilation

Citation

SuperSurv citation info

Materials

README

CRAN Checks

SuperSurv results [issues need fixing before 2026-06-10]

SuperSurv results

Reference Manual

SuperSurv.html , SuperSurv.pdf

SuperSurv.html SuperSurv.pdf

Vignettes

06. Machine Learning with Random Survival Forests ( source , R code ) 09. Causal Effects and Adjusted Marginal Contrasts (RMST) ( source , R code ) 11. Extending SuperSurv ( source , R code ) 05. Advanced Hyperparameter Tuning & Grid Search ( source , R code ) 00. Installation & Setup ( source , R code ) 02. Model Performance & Benchmarking ( source , R code ) 07. Parametric Survival Models ( source , R code ) 10. Scaling Up with Parallel Processing ( source , R code ) 04. High-Dimensional Data & Variable Screening ( source , R code ) 08. Interpreting the Black Box with SHAP & survex ( source , R code ) 03. Ensemble vs. Best Model Selection ( source , R code ) 01. SuperSurv with Ensemble ( source , R code )

Package Source

SuperSurv_0.1.2.tar.gz

Windows Binaries

r-devel: SuperSurv_0.1.2.zip , r-release: SuperSurv_0.1.2.zip , r-oldrel: SuperSurv_0.1.2.zip

SuperSurv_0.1.2.zip SuperSurv_0.1.2.zip SuperSurv_0.1.2.zip

MacOS Binaries

r-release (arm64): SuperSurv_0.1.2.tgz , r-oldrel (arm64): SuperSurv_0.1.2.tgz , r-release (x86_64): SuperSurv_0.1.2.tgz , r-oldrel (x86_64): SuperSurv_0.1.2.tgz

SuperSurv_0.1.2.tgz SuperSurv_0.1.2.tgz SuperSurv_0.1.2.tgz SuperSurv_0.1.2.tgz

Old Sources

SuperSurv archive

Page sections 3

Documentation

Heading

Documentation

Links

[{"label":"SuperSurv.html","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/refman/SuperSurv.html"},{"label":"SuperSurv.pdf","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/SuperSurv.pdf"},{"label":"06. Machine Learning with Random Survival Forests","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/base-learner-rfsrc.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/base-learner-rfsrc.Rmd"},{"label":"R code","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/base-learner-rfsrc.R"},{"label":"09. Causal Effects and Adjusted Marginal Contrasts (RMST)","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/causal-rmst.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/causal-rmst.Rmd"},{"label":"R code","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/causal-rmst.R"},{"label":"11. Extending SuperSurv","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/extending-supersurv.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/extending-supersurv.Rmd"},{"label":"R code","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/extending-supersurv.R"},{"label":"05. Advanced Hyperparameter Tuning \u0026 Grid Search","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/grid-search.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/grid-search.Rmd"},{"label":"R code","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/grid-search.R"},{"label":"00. Installation \u0026 Setup","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/installation.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/installation.Rmd"},{"label":"R code","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/installation.R"},{"label":"02. Model Performance \u0026 Benchmarking","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/model-performance.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/model-performance.Rmd"},{"label":"R code","section":"","type":"","url":"https://cran.r-project.org/web/packages/SuperSurv/vignettes/model-performance.R"}]

Text

Reference manual: SuperSurv.html , SuperSurv.pdf Vignettes: 06. Machine Learning with Random Survival Forests ( source , R code ) 09. Causal Effects and Adjusted Marginal Contrasts (RMST) ( source , R code ) 11. Extending SuperSurv ( source , R code ) 05. Advanced Hyperparameter Tuning & Grid Search ( source , R code ) 00. Installation & Setup ( source , R code ) 02. Model Performance & Benchmarking ( source , R code ) 07. Parametric Survival Models ( source , R code ) 10. Scaling Up with Parallel Processing ( source , R code ) 04. High-Dimensional Data & Variable Screening ( source , R code ) 08. Interpreting the Black Box with SHAP & survex ( source , R code ) 03. Ensemble vs. Best Model Selection ( source , R code ) 01. SuperSurv with Ensemble ( source , R code )

Downloads

Heading

Downloads

Links

[{"label":"SuperSurv_0.1.2.tar.gz","section":"","type":"","url":"https://cran.r-project.org/src/contrib/SuperSurv_0.1.2.tar.gz"},{"label":"SuperSurv_0.1.2.zip","section":"","type":"","url":"https://cran.r-project.org/bin/windows/contrib/4.7/SuperSurv_0.1.2.zip"},{"label":"SuperSurv_0.1.2.zip","section":"","type":"","url":"https://cran.r-project.org/bin/windows/contrib/4.6/SuperSurv_0.1.2.zip"},{"label":"SuperSurv_0.1.2.zip","section":"","type":"","url":"https://cran.r-project.org/bin/windows/contrib/4.5/SuperSurv_0.1.2.zip"},{"label":"SuperSurv_0.1.2.tgz","section":"","type":"","url":"https://cran.r-project.org/bin/macosx/sonoma-arm64/contrib/4.6/SuperSurv_0.1.2.tgz"},{"label":"SuperSurv_0.1.2.tgz","section":"","type":"","url":"https://cran.r-project.org/bin/macosx/big-sur-arm64/contrib/4.5/SuperSurv_0.1.2.tgz"},{"label":"SuperSurv_0.1.2.tgz","section":"","type":"","url":"https://cran.r-project.org/bin/macosx/big-sur-x86_64/contrib/4.6/SuperSurv_0.1.2.tgz"},{"label":"SuperSurv_0.1.2.tgz","section":"","type":"","url":"https://cran.r-project.org/bin/macosx/big-sur-x86_64/contrib/4.5/SuperSurv_0.1.2.tgz"},{"label":"SuperSurv archive","section":"","type":"","url":"https://CRAN.R-project.org/src/contrib/Archive/SuperSurv"}]

Text

Package source: SuperSurv_0.1.2.tar.gz Windows binaries: r-devel: SuperSurv_0.1.2.zip , r-release: SuperSurv_0.1.2.zip , r-oldrel: SuperSurv_0.1.2.zip macOS binaries: r-release (arm64): SuperSurv_0.1.2.tgz , r-oldrel (arm64): SuperSurv_0.1.2.tgz , r-release (x86_64): SuperSurv_0.1.2.tgz , r-oldrel (x86_64): SuperSurv_0.1.2.tgz Old sources: SuperSurv archive

Linking

Heading

Linking

Links

[{"label":"https://CRAN.R-project.org/package=SuperSurv","section":"","type":"","url":"https://CRAN.R-project.org/package=SuperSurv"}]

Text

Please use the canonical form https://CRAN.R-project.org/package=SuperSurv to link to this page.

Materials 1

README

Documentation 38

Vignettes 36

Downloads 9

SuperSurv_0.1.2.tar.gz SuperSurv_0.1.2.zip SuperSurv_0.1.2.zip SuperSurv_0.1.2.zip SuperSurv_0.1.2.tgz SuperSurv_0.1.2.tgz SuperSurv_0.1.2.tgz SuperSurv_0.1.2.tgz SuperSurv archive

All page links 82

survival nnls future.apply stats dplyr magrittr aorsf BART CoxBoost glmnet gbm mgcv randomForestSRC ranger rpart survivalsvm xgboost survex ggplot2 tidyr quadprog ggforce patchwork knitr rmarkdown 10.32614/CRAN.package.SuperSurv https://github.com/yuelyu21/SuperSurv/issues MIT LICENSE https://github.com/yuelyu21/SuperSurv https://yuelyu21.github.io/SuperSurv/SuperSurv citation info README SuperSurv results SuperSurv.html SuperSurv.pdf 06. Machine Learning with Random Survival Forests source R code 09. Causal Effects and Adjusted Marginal Contrasts (RMST)source R code 11. Extending SuperSurv source R code 05. Advanced Hyperparameter Tuning & Grid Search source R code 00. Installation & Setup source R code 02. Model Performance & Benchmarking source R code 07. Parametric Survival Models source SuperSurv_0.1.2.tar.gz SuperSurv_0.1.2.zip SuperSurv_0.1.2.zip SuperSurv_0.1.2.zip SuperSurv_0.1.2.tgz SuperSurv_0.1.2.tgz SuperSurv_0.1.2.tgz SuperSurv_0.1.2.tgz SuperSurv archive R code 10. Scaling Up with Parallel Processing source R code 04. High-Dimensional Data & Variable Screening source R code 08. Interpreting the Black Box with SHAP & survex source R code 03. Ensemble vs. Best Model Selection source R code 01. SuperSurv with Ensemble source R code https://CRAN.R-project.org/package=SuperSurv

버전 이력

Repository	Version	Published	First seen	Last seen
CRAN	0.1.2	2026-05-04	2026-06-01	2026-06-11
CRAN	0.1.1	2026-03-26	2026-05-31	2026-06-11
CRAN	0.1.7		2026-06-22	2026-06-23

보안

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문헌 신호

표시할 OpenAlex 데이터가 없습니다.