Abstract Discrete hazard models are widely applied for the analysis of time-to-event outcomes that intrinsically discrete or grouped versions continuous event times. Commonly, one assumes effect explanatory variables on can be described by a linear predictor function. This, however, may not appropriate when non-linear effects interactions between occur in data. To address this issue, we propose...