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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 "fido" in publications use:'
type: software
license: GPL-3.0-only
title: 'fido: Bayesian Multinomial Logistic Normal Regression'
version: 1.1.1
identifiers:
- type: doi
  value: 10.32614/CRAN.package.fido
abstract: Provides methods for fitting and inspection of Bayesian Multinomial Logistic
  Normal Models using MAP estimation and Laplace Approximation as developed in Silverman
  et. Al. (2022) <https://www.jmlr.org/papers/v23/19-882.html>. Key functionality
  is implemented in C++ for scalability. 'fido' replaces the previous package 'stray'.
authors:
- family-names: Silverman
  given-names: Justin
  email: Justin.Silverman@psu.edu
- family-names: Nixon
  given-names: Michelle
  email: pistner@psu.edu
preferred-citation:
  type: article
  title: Bayesian Multinomial Logistic Normal Models through Marginally Latent Matrix-T
    Processes
  authors:
  - family-names: Silverman
    given-names: Justin D.
  - family-names: Roche
    given-names: Kimberly
  - family-names: Holmes
    given-names: Zachary C.
  - family-names: David
    given-names: Lawrence A.
  - family-names: Mukherjee
    given-names: Sayan
  year: '2022'
  volume: '23'
  journal: Journal of Machine Learning Research
  url: https://www.jmlr.org/papers/v23/19-882.html
repository: https://jsilve24.r-universe.dev
repository-code: https://github.com/jsilve24/fido
commit: a4e6c2c4b9104348b32122473c454ea223acbc4d
url: https://jsilve24.github.io/fido/
date-released: '2024-05-31'
contact:
- family-names: Nixon
  given-names: Michelle
  email: pistner@psu.edu