  We consider finite mixtures of generalized linear models with binary output.
We prove that cross moment (between the output and the regression variables)
until order 3 are sufficient to identify all parameters of the model. We
propose a least-squares estimation method based on those moments and we prove
the consistency and the Gaussian asymptotic behavior of the estimator. We
provide simulation results and comparisons with likelihood methods. Numerical
experiments were conducted using the R-package Morpheus that we developed for
our least-squares moment method and with the R-package flexmix for likelihood
methods. We then give some possible extensions to finite mixtures of
regressions with binary output including both continuous and categorical
covariates, and possibly longitudinal data.
