Accelerated Oblique Random Survival Forests
c(
person(given = "Byron",
family = "Jaeger",
role = c("aut", "cre"),
email = "bjaeger@wakehealth.edu",
comment = c(ORCID = "0000-0001-7399-2299")),
person(given = "Nicholas",
family = "Pajewski",
role = "ctb"),
person(given = "Sawyer",
family = "Welden",
role = "ctb",
email = "swelden@wakehealth.edu"),
person(given = "Christopher",
family = "Jackson",
email = "chris.jackson@mrc-bsu.cam.ac.uk",
role = "rev")
)
Fit, interpret, and make predictions with oblique random survival forests. Oblique decision trees are notoriously slow compared to their axis based counterparts, but 'aorsf' runs as fast or faster than axis-based decision tree algorithms for right-censored time-to-event outcomes. Methods to accelerate and interpret the oblique random survival forest are described in Jaeger et al., (2022) <arXiv:2208.01129>.
survival, survivalROC, ggplot2, testthat (>= 3.0.0), knitr,
rmarkdown, glmnet, covr, units, tibble
Byron Jaeger [aut, cre] (<https://orcid.org/0000-0001-7399-2299>),
Nicholas Pajewski [ctb],
Sawyer Welden [ctb],
Christopher Jackson [rev]

c(
person(given = "Byron",
family = "Jaeger",
role = c("aut", "cre"),
email = "bjaeger@wakehealth.edu",
comment = c(ORCID = "0000-0001-7399-2299")),
person(given = "Nicholas",
family = "Pajewski",
role = "ctb"),
person(given = "Sawyer",
family = "Welden",
role = "ctb",
email = "swelden@wakehealth.edu"),
person(given = "Christopher",
family = "Jackson",
email = "chris.jackson@mrc-bsu.cam.ac.uk",
role = "rev"),
person(given = "Marvin",
family = "Wright",
role = "rev"),
person(given = "Lukas",
family = "Burk",
role = "rev")
)
survival, SurvMetrics, ggplot2, testthat (>= 3.0.0), knitr,
rmarkdown, glmnet, covr, units, tibble
Byron Jaeger [aut, cre] (<https://orcid.org/0000-0001-7399-2299>),
Nicholas Pajewski [ctb],
Sawyer Welden [ctb],
Christopher Jackson [rev],
Marvin Wright [rev],
Lukas Burk [rev]

Rcpp, data.table, utils, stats, collapse

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