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

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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