jackknifeEB: Small Area Estimation method with Empirical Bayes and its...

In saebnocov: Small Area Estimation using Empirical Bayes without Auxiliary Variable

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

Description

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

Usage

jackknifeEB(data, method, opt, maxiter = 100, tol = 1e-05)

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)
maxiter	the Maximum iteration value with default 100
tol	Tolerance error value at iteration with default 0.00001

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

Examples

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

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

saebnocov documentation built on Sept. 5, 2022, 9:07 a.m.