Estimate theta and psi in multinomial mixture model
This function is used to estimate theta and psi in multinomial mixture model given the number of components k.
ParEst(data, d, k, TT = 1000)
data
: - data in matrix formation with n rows and p columnsd
: - number of categories for each variablek
: - number of componentsTT
: - number of iterations in Gibbs sampler, default value is 1000. T should be an even number for 'burn-in'.theta - vector of probability for each component
psi - specific probability for each variable in each component
# dimension parameters n<-200; p<-5; d<-rep(2,p); # generate complete data Complete<-GenerateData(n, p, d, k = 3) # mask percentage of data at MCAR Incomplete<-Complete Incomplete[sample(1:n*p,0.2*n*p,replace = FALSE)]<-NA # k identify K<-kIdentifier(data = Incomplete, d, TT = 10) Par<-ParEst(data = Incomplete, d, k = K$k_est, TT = 10)
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