inibestcubecov function

Preliminary parameter estimates for CUBE models with covariates

Compute preliminary parameter estimates for a CUBE model with covariates for all the three parameters. These estimates are set as initial values to start the E-M algorithm within maximum likelihood estimation.

inibestcubecov(m,ordinal,Y,W,Z)

Arguments

• m: Number of ordinal categories
• ordinal: Vector of ordinal responses
• Y: Matrix of selected covariates to explain the uncertainty parameter
• W: Matrix of selected covariates to explain the feeling parameter
• Z: Matrix of selected covariates to explain the overdispersion parameter

Returns

A vector (inibet, inigama, inialpha) of preliminary estimates of parameter vectors for $\pi = \pi(\bold{\beta})$, $\xi=\xi(\bold{\gamma})$, $\phi=\phi(\bold{\alpha})$, respectively, of a CUBE model with covariates for all the three parameters. In details, inibet, inigama and inialpha have length equal to NCOL(Y)+1, NCOL(W)+1 and NCOL(Z)+1, respectively, to account for an intercept term for each component.

Examples

data(relgoods)
m<-10 
naord<-which(is.na(relgoods$Tv))
nacovpai<-which(is.na(relgoods$Gender))
nacovcsi<-which(is.na(relgoods$year.12))
nacovphi<-which(is.na(relgoods$EducationDegree))
na<-union(union(naord,nacovpai),union(nacovcsi,nacovphi))
ordinal<-relgoods$Tv[-na]
Y<-relgoods$Gender[-na]
W<-relgoods$year.12[-na]
Z<-relgoods$EducationDegree[-na]
ini<-inibestcubecov(m,ordinal,Y,W,Z)
p<-NCOL(Y)
q<-NCOL(W)
inibet<-ini[1:(p+1)]               # Preliminary estimates for uncertainty 
inigama<-ini[(p+2):(p+q+2)]        # Preliminary estimates for feeling 
inialpha<-ini[(p+q+3):length(ini)] # Preliminary estimates for overdispersion

See Also

inibestcube, inibestcubecsi, inibestgama