Traj estimates a discrete mixture model for longitudinal data grouping. Groupings may represent distinct subpopulations or alternatively, components of a discrete approximation for a potentially complex data distribution.
Supported distributions are: censored (or regular) normal, zero inflated (or regular) Poisson, and Bernoulli distributions (logistic model). The censored normal model is useful for psychometric scale data, the zero inflated Poisson model useful for count data with more zeros than would be expected under the Poisson assumption, and the Bernoulli model useful for 0/1 data. The model is appropriate for data with average values changing smoothly as a function of the dependent variable (time, age, ...). Some sharp changes can be handled through the inclusion of time dependent covariates.