I have trained an FAMD model using data (which had required imputation using imputeFAMD). I then use this model to predict the FAMD projections of new out-of-sample individuals.
What would be the best way for imputing data for new individuals with missing variables? As a constraint, the FAMD model should not be retrained, meaning that I would not simply be adding the new out-of-sample individuals as supplementary individuals at the time of training FAMD. In other words, the sequence would be:
impute sample data >> train FAMD model >> impute data of new individual >> predict FAMD projection of new individual
Perhaps my question requires clarification, which I'd be glad to provide.