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survBootOutliers
View on CRAN: Click
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Download and install survBootOutliers package within the R console
Install from CRAN:
install.packages("survBootOutliers")
Install from Github:
library("remotes")
install_github("cran/survBootOutliers") Install by package version:
library("remotes")
install_version("survBootOutliers", "1.0") Attach the package and use:
library("survBootOutliers")
Maintained by
Joao Pinto
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All associated links for this package
First Published: 2018-05-28
Latest Update: 2018-05-28
Description:
Three new methods to perform outlier detection in a survival context. In total there are six methods provided, the first three methods are traditional residual-based outlier detection methods, the second three are the concordance-based. Package developed during the work on the two following publications: Pinto J., Carvalho A. and Vinga S. (2015) <doi:10.5220/0005225300750082>; Pinto J.D., Carvalho A.M., Vinga S. (2015) <doi:10.1007/978-3-319-27926-8_22>.
How to cite:
Joao Pinto (2018). survBootOutliers: Concordance Based Bootstrap Methods for Outlier Detection in Survival Analysis. R package version 1.0, https://cran.r-project.org/web/packages/survBootOutliers. Accessed 05 Jun. 2026.
Previous versions and publish date:
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Complete documentation for survBootOutliers
Functions, R codes and Examples using
the survBootOutliers R package
Some associated functions: displays.histogram . get.whas100.dataset . survBootOutliers .
Some associated R codes: Untitled.R . bootstraps_p.R . coxfit.R . dbht_p.R . display_histograms.R . getwhas100dataset.R . paod_t_onesided.R . survBootOutliers.R . wod_4_p.R . wod_4hist_k_p.R . wod_6.R . wod_coxdevianceresiduals.R . wod_coxld.R . wod_coxmartingaleresiduals.R . Full survBootOutliers package functions and examples
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