 
Dear R Users, R Core Team,

I currently wonder how to predict the probability of an event with new data resulting from a finite mixture.
I read the documentation of the flexmix package and the examples of applications provided on CRAN but I could not find how to predict (except "manually" but I am looking for a simpler solution) the final probability of the mixture (for each individual) with new data (I mean data different from the ones I used to build the model).

I should have missed something but basically, I am fitting a 2-components mixture model with logistic weights and logistic components (and different explanatory variables, no identifiability problem). The flexmix object is then used in predict() function with 'newdata' in argument, and the predictions with these new data are obviously different depending on the component which is assigned to new observations.

My question is: how can I access the information on clustering the new observations (if I understood well, predictions are the predictions of the event probability for each individual and each component, but these are not predictions for cluster assignment...) ?

Thank you very much in advance for your answers,
Sincerely,
Xavier M.


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