Package: sae2 1.2-1

Robert Fay

sae2: Small Area Estimation: Time-Series Models

Time series area-level models for small area estimation. The package supplements the functionality of the sae package. Specifically, it includes EBLUP fitting of the original Rao-Yu model, which in the original form did not have a spatial component. The package also offers a modified ('dynamic') version of the Rao-Yu model, replacing the assumption of stationarity. Both univariate and multivariate applications are supported. Of particular note is the allowance for covariance of the area-level sample estimates over time, as encountered in rotating panel designs such as the U.S. National Crime Victimization Survey or present in a time-series of 5-year estimates from the American Community Survey. Key references to the methods include J.N.K. Rao and I. Molina (2015, ISBN:9781118735787), J.N.K. Rao and M. Yu (1994) <doi:10.2307/3315407>, and R.E. Fay and R.A. Herriot (1979) <doi:10.1080/01621459.1979.10482505>.

Authors:Robert Fay [aut, cre], Mamadou Diallo [aut]

sae2_1.2-1.tar.gz
sae2_1.2-1.tar.gz(r-4.5-noble)sae2_1.2-1.tar.gz(r-4.4-noble)
sae2_1.2-1.tgz(r-4.4-emscripten)sae2_1.2-1.tgz(r-4.3-emscripten)
sae2.pdf |sae2.html
sae2/json (API)

# Install 'sae2' in R:
install.packages('sae2', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

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

1.30 score 2 stars 6 scripts 173 downloads 5 exports 11 dependencies

Last updated 1 years agofrom:7175c47d86. Checks:OK: 1 NOTE: 1. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 15 2024
R-4.5-linuxNOTENov 15 2024

Exports:eblupDyneblupRYgeo_ratiosmvrnormSeriesvcovgen

Dependencies:DBIlatticeMASSMatrixminqamitoolsnumDerivRcppRcppArmadillosurveysurvival