search for: dabipf

Hello all, When I used commands "ecm.mix and dabipf.mix" to do a simulation (sample size is small 100), I got an error : Steps of ECM, missing value where True/False needed. I've checked the menu, and the option "prior" of ecm.mix said that if structural zeros appear in the table, hyperparameters for those cells should be set to...

Hello, We use the mix package and we have a problem with the DA function. We aren't sure, but it's maybbe a memory problem. We have done: > Ent<--read.table("C:/.../File.txt") > attach(Ent) > Ent V1 V2 V3 V4 ... V16 V17 1 1 1 2 6 18 18 2 1 1 1 NA 14 17 3 1 1 2 1 16 14 .... 199 2 1 NA 7 19 18 200

I am desperately trying to impute missing data using 'imp.mix' but always run into this yucky error message to which I cannot find the solution. It's the first time I am using mix and I'm trying really hard to understand, but there's just this one step I don't get...perhaps someone knows the answer? Thanks! Jens My code runs:

...dom number generator seed margins<-c(1,2) #<-- I have two categorical variables, if I had three, the margin=c(1,2,3) design<-matrix(c(1,1,1,1,0,1,0,1,0,0,1,1),ncol=3) for (i in 1:5){ cat("Doing imputation ",i,"\n") thetahat <- ecm.mix(s,margins,design) newtheta <- dabipf.mix(s, margins,design,thetahat, steps=2000, showits=TRUE) MI[[i]] <- imp.mix(s, newtheta) } Steps of ECM: 1...2...3...4...5...6...7...8...9...10...11...12...13...14...15...16...17... 18...19...20...21...22...23...24...25...26... Steps of Data Augmentation-Bayesian IPF: 1...2...Error: NA/NaN/I...

...Fit Generalized Linear Mixed Models via PQL gamm(mgcv) Generalized Additive Mixed Models gamm.setup(mgcv) Generalized Additive Mixed Model set up. da.mix(mix) Data Augmentation for Unrestricted General Location Model dabipf.mix(mix) Data Augmentation/Bayesian IPF Algorithm for Restricted General Location Models ecm.mix(mix) ECM Algorithm for Restricted General Location Model em.mix(mix) EM Algorithm for Unrestricted General Loc...