mspe_PMS_Mis_FH_SUMCA {SumcaVer1}R Documentation

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

Description

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

Usage

mspe_PMS_Mis_FH_SUMCA(m, p, X, beta1, beta2, A, D, K, R)

Arguments

m

number of small areas

p

number of fixed model parameters

X

covariates

beta1

regression coefficient

beta2

regression coefficient

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


[Package SumcaVer1 version 0.1.0 Index]