# ------------------------------------------------
# CITATION.cff file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# ------------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "interSAE" in publications use:'
type: software
license: MIT
title: 'interSAE: Intersectional Small Area Estimation from Survey and Census Data'
version: 0.1.0
identifiers:
- type: doi
  value: 10.32614/CRAN.package.interSAE
abstract: Implements design-aware, margin-constrained estimation of population indicators
  for geographic areas crossed with demographic subgroups. Complex-survey microdata
  supply outcomes and association information, while one or more aggregate census
  tables supply overlapping population margins. A generalized iterative proportional
  fitting engine reconstructs a coherent latent population table, and an augmented
  model-assisted estimator produces domain means, proportions, and totals for sampled
  and unsampled intersections. Tools diagnose non-identification, compute linear-programming
  sensitivity bounds, propagate sampling and model uncertainty with replicate-weight
  or multiplier bootstrap procedures, enforce structural zeros, and benchmark estimates
  to official totals. The framework extends calibration ideas from Deville and Sarndal
  (1992) <https://doi.org/10.1080/01621459.1992.10475217> and small area estimation
  ideas from Fay and Herriot (1979) <https://doi.org/10.1080/01621459.1979.10482505>.
authors:
- family-names: Marvian Mashhad
  given-names: Leila
  email: leila.marveian@gmail.com
preferred-citation:
  type: manual
  title: 'interSAE: Intersectional Small Area Estimation from Survey and Census Data'
  authors:
  - family-names: Marvian Mashhad
    given-names: Leila
    email: leila.marveian@gmail.com
  year: '2026'
  notes: R package version 0.1.0
repository: https://leilamarvian.r-universe.dev
commit: a6f3bf9e320986673f55e6f4d5236d2b7d5bfc7c
date-released: '2026-08-25'
contact:
- family-names: Marvian Mashhad
  given-names: Leila
  email: leila.marveian@gmail.com