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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 "spDBL" in publications use:'
type: software
license: MIT
title: 'spDBL: Dynamic Bayesian Learning for Spatiotemporal Mechanistic Models'
version: 1.0.2
abstract: Provides tools for Bayesian learning of spatiotemporal dynamical mechanistic
  models. Includes methods for parameter estimation, simulation, and inference using
  hierarchical and state-space modeling approaches, following Banerjee, Chen, Frankenburg
  and Zhou (2025) <https://jmlr.org/papers/v26/22-0896.html>.
authors:
- family-names: Chen
  given-names: Xiang
  email: xiangchen@ucla.edu
- family-names: Banerjee
  given-names: Sudipto
  email: sudipto@ucla.edu
preferred-citation:
  type: article
  title: Dynamic Bayesian Learning for Spatiotemporal Mechanistic Models
  authors:
  - family-names: Banerjee
    given-names: Sudipto
    email: sudipto@ucla.edu
  - family-names: Chen
    given-names: Xiang
    email: xiangchen@ucla.edu
  - family-names: Frankenburg
    given-names: Ian
  - family-names: Zhou
    given-names: Daniel
  journal: Journal of Machine Learning Research
  volume: '26'
  issue: '146'
  year: '2025'
  url: https://jmlr.org/papers/v26/22-0896.html
  start: '1'
  end: '43'
repository: https://cran.r-universe.dev
commit: ce91035c804b0c25514ecc18212184d23b5d285b
date-released: '2026-06-09'
contact:
- family-names: Chen
  given-names: Xiang
  email: xiangchen@ucla.edu