<?xml version="1.0" encoding="UTF-8"?>
<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:title>Poisson Super Learner</dc:title>
  <dc:title>R package poissonsuperlearner version 0.1.1</dc:title>
  <dc:description>Provides tools for fitting piece-wise constant hazard models for survival and competing risks data, including ensemble hazard estimation via the Super Learner framework. The package supports estimation of survival functions and absolute risk predictions from fitted cause-specific hazard models. For the Super Learner framework see van der Laan, Polley and Hubbard (2007) &lt;doi:10.2202/1544-6115.1309&gt;.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Depends: data.table, sampling, riskRegression</dc:relation>
  <dc:relation>Imports: Rcpp, methods, lava, Matrix, glmnet, mgcv</dc:relation>
  <dc:relation>LinkingTo: Rcpp</dc:relation>
  <dc:relation>Suggests: knitr, rmarkdown, survival, prodlim, testthat (&gt;= 3.0.0)</dc:relation>
  <dc:creator>Gabriele Pittarello &lt;gabriele.pittarello@sund.ku.dk&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Gabriele Pittarello [aut, cre],
  Helene Rytgaard [aut],
  Thomas Gerds [aut]</dc:contributor>
  <dc:rights>GPL (&gt;= 2)</dc:rights>
  <dc:date>2026-04-04</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=poissonsuperlearner</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.poissonsuperlearner</dc:identifier>
</oai_dc:dc>
