| sae2-package {sae2} | R Documentation |
Small Area Estimation: Time-Series Models.
Description
Time series are-level models for small area estimation.
The package supplements the functionality of the package sae.
Specifically, it includes EBLUP fitting of the original
Rao-Yu model, which did not have a spatial component. It 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.
Details
| Package: | sae2 |
| Type: | Package |
| Version: | 1.2-1 |
| Date: | 2023-08-22 |
| License: | GPL-2 |
The package provides two primary functions, eblupRY and eblupDyn,
to fit non-spatial time-series small area models to area-level data. The
function mvrnormSeries provides simulated data under either model.
Functions geo_ratios and vcovgen can assist in preparing the
input.
Author(s)
Robert E. Fay, Mamadou S. Diallo
Maintainer: Robert E. Fay <bobfay@hotmail.com>
References
- Fay, R.E. and Herriot, R.A. (1979). Estimation of income from small places: An application of James-Stein procedures to census data. Journal of the American Statistical Association 74, 269-277.
- Fay, R.E., Planty, M. and Diallo, M.S. (2013). Small area estimates from the National Crime Victimization Survey. Proceedings of the Joint Statistical Meetings. American Statistical Association, pp. 1544-1557.
- Rao, J.N.K. and Molina, I. (2015). Small Area Estimation, 2nd ed. Wiley, Hoboken, NJ.
- Rao, J.N.K. and Yu, M. (1994). Small area estimation by combining time series and cross-sectional data. Canadian Journal of Statistics 22, 511-528.