Package: saeME 1.3.1
Muhammad Rifqi Mubarak
saeME: Small Area Estimation with Measurement Error
A set of functions and datasets implementation of small area estimation when auxiliary variable is measured with error. These functions provide a empirical best linear unbiased prediction (EBLUP) estimator and mean squared error (MSE) estimator of the EBLUP. These models were developed by Ybarra and Lohr (2008) <doi:10.1093/biomet/asn048>.
Authors:
saeME_1.3.1.tar.gz
saeME_1.3.1.tar.gz(r-4.5-noble)saeME_1.3.1.tar.gz(r-4.4-noble)
saeME_1.3.1.tgz(r-4.4-emscripten)saeME_1.3.1.tgz(r-4.3-emscripten)
saeME.pdf |saeME.html✨
saeME/json (API)
# Install 'saeME' in R: |
install.packages('saeME', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 1 years agofrom:ec44e009e7. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 14 2024 |
R-4.5-linux | OK | Oct 14 2024 |
Dependencies:MASS
Readme and manuals
Help Manual
Help page | Topics |
---|---|
saeME: Small Area Estimation with Measurement Error | saeME-package saeME |
dataME | dataME |
datamix | datamix |
Fay-Herriot Model with Measurement Error | FHme |
Mean Squared Error Estimator of the EBLUP under a Fay-Herriot Model with Measurement Error | mse_FHme |