| EBnaive {saebnocov} | R Documentation |
Small Area Estimation method with Empirical Bayes and its RRMSE value by Naive Method
Description
Small Area Estimation method with Empirical Bayes and its RRMSE value by Naive Method
Usage
EBnaive(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 estimatior and EB estimator in each area |
estimation |
an information about EB estimator and its RRMSE value obtained by Naive method |
parameter |
Alpha and beta estimator |
pcap |
pcap (the weighted sample mean), vardir (the weighted sample variance),yt (the total number of the "success" category from each area), and nt (the total number of sample from each area) |
dir.est |
an information about direct estimator |
Examples
## load dataset with no weight value
data(dataEB)
## Calculates EB estimator
## with its RRMSE value by Naive method.
## Its alpha and beta estimator obtained
## by Moment method by J.N.K.Rao
EBnaive(data = dataEB[,-c(3)],method = "rao",opt = "moment", maxiter = 100, tol = 1e-5)
##load dataset with weight value
data(dataEB)
## Calculates EB estimator
## with its RRMSE value by Naive method.
## Its alpha and beta estimator obtained
## by Moment method by Claire E.B.O.
EBnaive(data = dataEB, method = "claire",opt = "moment", maxiter = 100, tol = 1e-5)