phi.mult {mme}

Initial values for the variance components for Model 1

Description

This function is used in initial.values to calculate the initial values for the variance components in the multinomial mixed model with one independent random effect in each category of the response variable (Model 1).

Usage

phi.mult(beta.0, y, Xk, M)

Arguments

beta.0

initial values for the fixed effects obtained in initial.values.

y

matrix with the response variable obtained from data.mme. The rows are the domains and the columns are the categories of the response variable.

Xk

list of matrices with the auxiliary variables per category obtained from data.mme. The dimension of the list is the number of domains.

M

vector with the sample size of the areas.

Value

phi.0 vector of inicial values for the variance components

References

Lopez-Vizcaino, ME, Lombardia, MJ and Morales, D (2013). Multinomial-based small area estimation of labour force indicators. Statistical Modelling, 13, 153-178.

See Also

data.mme, initial.values, wmatrix, prmu, Fbetaf, phi.direct, sPhikf, ci, modelfit1, msef, mseb.

Examples

k=3 #number of categories of the response variable
pp=c(1,1) #vector with the number of auxiliary variables in each category
data(simdata) #data
mod=1 #type of model
datar=data.mme(simdata,k,pp,mod)
###beta values
beta.new=list()
beta.new[[1]]=matrix(c( 1.3,-1),2,1)
beta.new[[2]]=matrix(c( -1.6,1),2,1)

##Initial variance components
phi=phi.mult(beta.new,datar$y,datar$Xk,datar$n)