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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "boostmtree" in publications use:'
type: software
license: GPL-3.0-or-later
title: 'boostmtree: Boosted Multivariate Trees for Longitudinal Data'
version: 1.5.1
identifiers:
- type: doi
  value: 10.32614/CRAN.package.boostmtree
abstract: Implements Friedman's gradient descent boosting algorithm for modeling longitudinal
  response using multivariate tree base learners. Longitudinal response could be continuous,
  binary, nominal or ordinal. A time-covariate interaction effect is modeled using
  penalized B-splines (P-splines) with estimated adaptive smoothing parameter. Although
  the package is design for longitudinal data, it can handle cross-sectional data
  as well. Implementation details are provided in Pande et al. (2017), Mach Learn
  <DOI:10.1007/s10994-016-5597-1>.
authors:
- family-names: Kogalur
  given-names: Udaya B.
  email: ubk@kogalur.com
- family-names: Ishwaran
  given-names: Hemant
  email: hemant.ishwaran@gmail.com
- family-names: Pande
  given-names: Amol
  email: amoljpande@gmail.com
preferred-citation:
  type: manual
  title: Boosted Multivariate Trees for Longitudinal Data
  authors:
  - family-names: Ishwaran
    given-names: H.
  - family-names: Pande
    given-names: A.
  - family-names: Kogalur
    given-names: U.B.
  publisher:
    name: manual
  year: '2022'
  notes: R package version 1.5.1
  url: https://cran.r-project.org/package=boostmtree
repository: https://cranhaven.r-universe.dev
commit: 67d41fad8be84f7226ff7613ceef56115352b3b2
url: https://ishwaran.org/ishwaran.html
date-released: '2022-03-09'
contact:
- family-names: Kogalur
  given-names: Udaya B.
  email: ubk@kogalur.com