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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 "spTimer" in publications use:'
type: software
license: GPL-2.0-or-later
title: 'spTimer: Spatio-Temporal Bayesian Modelling'
version: 3.3.3
doi: 10.18637/jss.v063.i15
identifiers:
- type: doi
  value: 10.32614/CRAN.package.spTimer
abstract: Fits, spatially predicts and temporally forecasts large amounts of space-time
  data using [1] Bayesian Gaussian Process (GP) Models, [2] Bayesian Auto-Regressive
  (AR) Models, and [3] Bayesian Gaussian Predictive Processes (GPP) based AR Models
  for spatio-temporal big-n problems. Bakar and Sahu (2015) <https://doi.org/10.18637/jss.v063.i15>.
authors:
- family-names: Bakar
  given-names: K. Shuvo
  email: shuvo.bakar@gmail.com
  orcid: https://orcid.org/0000-0003-3215-4496
preferred-citation:
  type: article
  title: 'spTimer: Spatio-Temporal Bayesian Modeling Using R'
  authors:
  - family-names: Bakar
    given-names: K. Shuvo
    email: shuvo.bakar@gmail.com
    orcid: https://orcid.org/0000-0003-3215-4496
  - family-names: Sahu
    given-names: Sujit K.
  year: '2015'
  journal: Journal of Statistical Software
  doi: 10.18637/jss.v063.i15
  url: https://doi.org/10.18637/jss.v063.i15
  volume: '63'
  issue: '15'
  start: '1'
  end: '32'
repository: https://CRAN.R-project.org/package=spTimer
date-released: '2024-09-05'
contact:
- family-names: Bakar
  given-names: K. Shuvo
  email: shuvo.bakar@gmail.com
  orcid: https://orcid.org/0000-0003-3215-4496