We present a framework for statistical analysis of discrete event systems which combines tools such as simulation of marked point processes, likelihood methods, kernel density estimation and stochastic approximation to enable statistical analysis of the discrete event system, even if...

To enable answering the question in the title, we introduce a bivariate censored latent effects autoregression, and discuss representation, parameter estimation, diagnostics and inference. We show that this bivariate nonlinear model is very useful for examining common nonlinearity. We apply the...