Package: saery 2.0

saery: Small Area Estimation for Rao and Yu Model

Functions to calculate EBLUPs (Empirical Best Linear Unbiased Predictor) estimators and their MSEs (Mean Squared Errors). Estimators are based on an area-level linear mixed model introduced by Rao and Yu (1994) <doi:10.2307/3315407>. The REML (Residual Maximum Likelihood) method is used for fitting the model.

Authors:Cabello E. [aut], Esteban M.D. [aut], Morales Domingo [aut], Perez Agustin [aut, cre]

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saery.pdf |saery.html✨
saery/json (API)

# Install 'saery' in R:
install.packages('saery', repos = c('https://small-area-estimation.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • datos - Dataset for saery package

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 1 stars 5 scripts 519 downloads 8 exports 0 dependencies

Last updated 1 months agofrom:edc63e704b. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 11 2025
R-4.5-winOKMar 11 2025
R-4.5-macOKMar 11 2025
R-4.5-linuxOKMar 11 2025
R-4.4-winOKMar 11 2025
R-4.4-macOKMar 11 2025
R-4.4-linuxOKMar 11 2025
R-4.3-winOKMar 11 2025
R-4.3-macOKMar 11 2025

Exports:eblup.saeryeblup.saery.AR1eblup.saery.indepeblup.saery.MA1fit.saeryfit.saery.AR1fit.saery.indepfit.saery.MA1

Dependencies: