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# CITATION.cff 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 "spconform" in publications use:'
type: software
license: GPL-3.0-only
title: 'spconform: Conformal Prediction for Spatially and Spatio-Temporally Dependent
  Data'
version: 0.1.2
doi: 10.32614/CRAN.package.spconform
identifiers:
- type: doi
  value: 10.32614/CRAN.package.spconform
abstract: Provides distribution-free, model-agnostic prediction intervals for spatially
  and spatio-temporally dependent data using localized conformal calibration. Implements
  locally weighted split conformal prediction for geostatistical (point-referenced)
  data based on spatial-distance kernels, and a neighbourhood-weighted conformal procedure
  for areal (lattice) data based on graph adjacency structures. Relaxes the standard
  exchangeability assumption using spatial proximity, following the localized conformal
  framework of Mao, Martin and Reich (2024) <https://doi.org/10.1080/01621459.2022.2147531>.
  Includes comprehensive spatial diagnostic tools to audit empirical coverage, conditional
  spatial strata, and boundary proximity effects.
authors:
- family-names: Jabbar
  given-names: Ahmed Sattar
  email: ahmed.state.me@gmail.com
  orcid: https://orcid.org/0009-0006-4614-735X
preferred-citation:
  type: manual
  title: 'spconform: Conformal Prediction for Spatially and Spatio-Temporally Dependent
    Data'
  authors:
  - family-names: Jabbar
    given-names: Ahmed Sattar
    email: ahmed.state.me@gmail.com
    orcid: https://orcid.org/0009-0006-4614-735X
  year: '2026'
  notes: R package version 0.1.2
  url: https://CRAN.R-project.org/package=spconform
  doi: 10.32614/CRAN.package.spconform
repository: https://amjed-droid.r-universe.dev
repository-code: https://github.com/amjed-droid/spconform
commit: 1069a842bf3fbe72be1367e306b56bfd23f718af
url: https://amjed-droid.github.io/spconform/
date-released: '2026-10-10'
contact:
- family-names: Jabbar
  given-names: Ahmed Sattar
  email: ahmed.state.me@gmail.com
  orcid: https://orcid.org/0009-0006-4614-735X