Dear R-users, i have the following exmple for which i want to use ecm.mix from the mix-package. with da.mix after using em.mix i get the error "improper posterior--empty cells", which is not uncommen because of 17 * 5 * 3 = 255 cells. so the next attempt is to use the ecm.mix for the restricted model, but i get errors also. what can i do to get the imputations with the mix package working? maybe it could be reasonable to merge some levels before imputation? best regards Andreas y <- matrix(0, nrow=100, ncol=4, byrow=TRUE) y[,1] <- sample(17,100,replace=TRUE) y[,2] <- sample(5,100,replace=TRUE) y[,3] <- sample(3,100,replace=TRUE) y[,4] <- rnorm(100) y[,1] <- ifelse(rbinom(100,1,0.4)==1, NA, y[,1]) y[,2] <- ifelse(rbinom(100,1,0.7)==1, NA, y[,2]) y[,3] <- ifelse(rbinom(100,1,0.05)==1, NA, y[,3]) ## first attempt, imputation under unrestricted model s <- prelim.mix(y,3) thetahat <- em.mix(s) rngseed(1234567) # set random number generator seed newtheta <- da.mix(s,thetahat,steps=100) # data augmentation ##ximp <- imp.mix(s, newtheta, y) ## da.mix gives "improper posterior--empty cells" error ## second attempt, imputation under restricted model s <- prelim.mix(y,3) margins1 <- c(1,2,3) margins2 <- c(1,2,0,2,3,0,1,3) design <- diag(rep(1,255)) # identity matrix D=no of cells thetahat <- ecm.mix(s,margins1,design) # find ML estimate thetahat <- ecm.mix(s,margins2,design) # find ML estimate #rngseed(1234567) # random generator seed #newtheta <- dabipf.mix(s,margins,design,thetahat,steps=200) #ximp <- imp.mix(s,newtheta,stlouis) # impute under newtheta