EBnaive {saebnocov} | R Documentation |
Small Area Estimation method with Empirical Bayes and its RRMSE value by Naive Method
EBnaive(data, method, opt, maxiter = 100, tol = 1e-05)
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 |
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 |
## 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)