bootstrapEB {saebnocov}

Small Area Estimation method with Empirical Bayes and its RRMSE value by Bootstrap Method

Description

Small Area Estimation method with Empirical Bayes and its RRMSE value by Bootstrap Method

Usage

bootstrapEB(data, method, opt, seed = NA, maxiter = 25, tol = 1e-05, B = 50)

Arguments

data

the data must contain two or three columns : code, y, and weight data if exist.

method

Method to estimate alpha and beta parameter according to person(rao or claire)

opt

Method to estimate alpha and beta parameter according to the way of calculation (moment or nr)

seed

Setting a seed in set.seed() function to initialize a pseudorandom number generator with default number 0

maxiter

the Maximum iteration value with default 100

tol

Tolerance error value at iteration with default 0.00001

B

The number of iteration of bootstrap resampling with default 200

Value

This function returns a list with following objects :

finalres

an information about direct estimator and EB estimator in each area with its RRMSE value obtained by bootstrap method

eb.estimation

an information about EB estimator in each area with its RRMSE value obtained by Naive method

References

Rao J, Peralta IM (2015). Small Area Estimation Second Edition. John Wiley & Sons, Inc.,Hoboken, New Jersey, Canada. ISBN 978-1-118-73578-7.

Examples

## load dataset with no weight value
data(dataEB)
## Calculates EB estimator with its
## RRMSE value by Bootstrap method.
## Its alpha and beta estimator obtained
## by Moment method by J.N.K.Rao
bootstrapEB(data = dataEB[,-c(3)], method = "rao",
 opt = "moment", maxiter = 20, tol = 1e-5,B=20,seed=0)

##load dataset with weight value
data(dataEB)
## Calculates EB estimator with its
## RRMSE value by Bootstrap method.
## Its alpha and beta estimator obtained
## by Moment method by Claire E.B.O.
bootstrapEB(data = dataEB, method = "rao",
 opt = "moment", maxiter = 20, tol = 1e-5,B=20,seed=0)