# saery-package: Small Area Estimation for Rao and Yu model In saery: Small Area Estimation for Rao and Yu Model

## Description

A complete set of functions to calculate several eblups estimators and its mean square errors. All estimators are based in area-level linear mixed model introduced by Rao and Yu in 1994 (see documentation). Saery package are developed to fit the model with REML method.

## Details

 Package: saery Type: Package Version: 1.0 Date: 2014-09-10 License: GPL-2

The main functions of the saery package are `fit.saery` and `eblup.saery`. The function `fit.saery` is used to fit the correct model for three options. `eblup.saery` calculates the eblup and mse for the model.

## Author(s)

Maria Dolores Esteban Lefler, Domingo Morales Gonzalez, Agustin Perez Martin

Maintainer: Agustin Perez Martin <agustin.perez@umh.es>

## References

Rao, J.N.K., Yu, M., 1994. Small area estimation by combining time series and cross sectional data. Canadian Journal of Statistics 22, 511-528.

Esteban, M.D., Morales, D., Perez, A., Santamaria, L., 2012. Small area estimation of poverty proportions under area-level time models. Computational Statistics and Data Analysis, 56 (10), pp. 2840-2855.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12``` ```sigma2edi <- datos[,6] X <- as.matrix(datos[,5]) ydi <- datos[,3] D <- length(unique(datos[,1])) md <- rep(length(unique(datos[,2])), D) output.fit.ar1 <- fit.saery(X, ydi, D, md, sigma2edi, "AR", 0.9) output.fit.ar1 #For computational reasons B is too low. We recomend to increase up to 100 eblup.output.ar1 <- eblup.saery(X, ydi, D, md, sigma2edi, "a", plot = TRUE, B = 2) eblup.output.ar1 ```

saery documentation built on May 2, 2019, 4:17 a.m.