inibestcubecsi function

Preliminary estimates of parameters for CUBE models with covariates only for feeling

Compute preliminary parameter estimates of a CUBE model with covariates only for feeling, given ordinal responses. These estimates are set as initial values to start the corresponding E-M algorithm within the package.

inibestcubecsi(m,ordinal,W,starting,maxiter,toler)

Arguments

• m: Number of ordinal categories
• ordinal: Vector of ordinal responses
• W: Matrix of selected covariates to explain the feeling component
• starting: Starting values for preliminary estimation of a CUBE without covariate
• maxiter: Maximum number of iterations allowed for preliminary iterations
• toler: Fixed error tolerance for final estimates for preliminary iterations

Returns

A vector (pai, gamaest, phi), where pai is the initial estimate for the uncertainty parameter, gamaest is the vector of initial estimates for the feeling component (including an intercept term in the first entry), and phi is the initial estimate for the overdispersion parameter.

Details

Preliminary estimates for the uncertainty and the overdispersion parameters are computed by short runs of EM. As to the feeling component, it considers the nested CUB model with covariates and calls inibestgama to derive initial estimates for the coefficients of the selected covariates for feeling.

Examples

data(relgoods)
isnacov<-which(is.na(relgoods$Gender))
isnaord<-which(is.na(relgoods$Tv))
na<-union(isnacov,isnaord)
ordinal<-relgoods$Tv[-na]; W<-relgoods$Gender[-na]
m<-10
starting<-rep(0.1,3)
ini<-inibestcubecsi(m,ordinal,W,starting,maxiter=100,toler=1e-3)
nparam<-length(ini)
pai<-ini[1]                 # Preliminary estimates for uncertainty component
gamaest<-ini[2:(nparam-1)]  # Preliminary estimates for coefficients of feeling covariates
phi<-ini[nparam]            # Preliminary estimates for overdispersion component

See Also

inibestcube, inibestcubecov, inibestgama