Package: maSAE 2.0.3.9000

maSAE: Mandallaz' Model-Assisted Small Area Estimators

An S4 implementation of the unbiased extension of the model- assisted synthetic-regression estimator proposed by Mandallaz (2013) <doi:10.1139/cjfr-2012-0381>, Mandallaz et al. (2013) <doi:10.1139/cjfr-2013-0181> and Mandallaz (2014) <doi:10.1139/cjfr-2013-0449>. It yields smaller variances than the standard bias correction, the generalised regression estimator.

Authors:Andreas Dominik Cullmann [aut, cre], Daniel Mandallaz [ctb], Alexander Francis Massey [ctb]

maSAE_2.0.3.9000.tar.gz
maSAE_2.0.3.9000.zip(r-4.5)maSAE_2.0.3.9000.zip(r-4.4)maSAE_2.0.3.9000.zip(r-4.3)
maSAE_2.0.3.9000.tgz(r-4.4-any)maSAE_2.0.3.9000.tgz(r-4.3-any)
maSAE_2.0.3.9000.tar.gz(r-4.5-noble)maSAE_2.0.3.9000.tar.gz(r-4.4-noble)
maSAE_2.0.3.9000.tgz(r-4.4-emscripten)maSAE_2.0.3.9000.tgz(r-4.3-emscripten)
maSAE.pdf |maSAE.html✨
maSAE/json (API)
NEWS

# Install 'maSAE' in R:
install.packages('maSAE', repos = c('https://fvafrcu.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://gitlab.com/fvafrcu/masae

Datasets:
  • s0 - Example s0 Data Set
  • s1 - Example s1 Data Set
  • s2 - Example s2 Data Set

On CRAN:

3.70 score 8 scripts 720 downloads 3 exports 0 dependencies

Last updated 4 years agofrom:de7d8cafb0. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 06 2024
R-4.5-winOKNov 06 2024
R-4.5-linuxOKNov 06 2024
R-4.4-winOKNov 06 2024
R-4.4-macOKNov 06 2024
R-4.3-winOKNov 06 2024
R-4.3-macOKNov 06 2024

Exports:bind_datapredictsaObj

Dependencies:

Mandallaz' model-assisted small area estimators

Rendered frommaSAE.Rnwusingutils::Sweaveon Nov 06 2024.

Last update: 2020-03-11
Started: 2016-02-24