bootstrapEB {saebnocov} | R Documentation |
Small Area Estimation method with Empirical Bayes and its RRMSE value by Bootstrap Method
bootstrapEB(data, method, opt, seed = NA, maxiter = 25, tol = 1e-05, B = 50)
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 |
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 |
Rao J, Peralta IM (2015). Small Area Estimation Second Edition. John Wiley & Sons, Inc.,Hoboken, New Jersey, Canada. ISBN 978-1-118-73578-7.
## 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)