mspe_PMS_FH_SUMCA {SumcaVer1}

Post model selection MSPE estimation in FH model using SUMCA method. Calculate the post-model selection mspe of Fay-Herriot model using SUMCA method.

Description

Post model selection MSPE estimation in FH model using SUMCA method. Calculate the post-model selection mspe of Fay-Herriot model using SUMCA method.

Usage

mspe_PMS_FH_SUMCA(m, p, X, beta, A, D, K, R)

Arguments

m

number of small areas

p

number of fixed model parameters

X

covariates

beta

regression coefficients

A

variance of area-specific random effects

D

sampling variance

K

number of Monte Carlo for the SUMCA method

R

number of simulation runs

Value

Par: return estimation of model parameters

MSPE.TRUE.Final: return empirical MSPE of small area predictor

mspe.Sumca.Final: return mspe of small area predictor using the SUMCA method

RB.SUMCA: return relative bias (RB) of mspe of small area predictor using the SUMCA method

Examples

mspe_PMS_FH_SUMCA(20,3,matrix(runif(60,0,1),nrow=20,byrow=TRUE),
c(1,1,1),10,2.5,10,10)