hbsae (version 1.0)

fSAE.Area: Compute small area estimates based on the basic area-level model.

Description

This function returns small area estimates based on the basic area-level model, also known as the Fay-Herriot model. It calls fSAE.Unit to carry out the computations.

Usage

fSAE.Area(est.init, var.init, X, x = X, ...)

Arguments

est.init

m-vector of initial estimates, where m is the number of sampled areas.

var.init

m-vector of corresponding variance estimates.

X

M x p matrix of area population means, where M is the number of areas for which estimates are required.

x

defaults to X, but in case auxiliary information is available at the unit level, it may be set to the corresponding matrix of covariate sample means.

...

additional arguments passed to fSAE.Unit.

Value

An object of class sae containing the small area estimates and MSEs, the model fit, and model selection measures.

References

R.E. Fay and R.A. Herriot (1979). Estimates of Income for Small Places: An Application of James-Stein Procedures to Census Data. Journal of the American Statistical Association 74(366), 269-277.

J.N.K. Rao (2003). Small Area Estimation. Wiley.

See Also

sae-class

Examples

# NOT RUN {
d <- generateFakeData()

# first compute input estimates without "borrowing strength" over areas
sae0 <- fSAE(y0 ~ x + area2, data=d$sam, area="area", popdata=d$Xpop, type="direct", keep.data=TRUE)

# compute small area estimates based on the basic area-level model
#   using the above survey regression estimates as input
sae <- fSAE.Area(EST(sae0), MSE(sae0), X=sae0$Xp)
EST(sae)  # estimates
SE(sae)  # standard errors
# }