For a simplified structural equation/IV regression model with one right-side endogenous variable, we obtain the exact conditional distribution function for Moreira's (2003) conditional likelihood ratio (CLR) test. This is then used to obtain the critical value function needed to implement the...

Complex designs are often used to select the sample which is followed over time in a panel survey. We consider some parametric models for panel data and discuss methods of estimating the model parameters which allow for complex schemes. We incorporate survey weights into alternative point...

Bayesian models for computer-aided underwriting have been developed for a major composite insurance company for two classes of commercial business: motor fleet and fire. The fire model produces a posterior probability distribution over a discretized dimension of risk, defined as the probability...

Presents a latent trait and a latent class model for analyzing the relationships among a set of mixed manifest variables using 1 or more latent variables. The set of manifest variables contains metric (continuous or discrete) and binary items. For the latent trait model the latent variables are...

Simulating the outcome of an intervention is a central problem in many fields as this allows decision-makers to quantify the effect of any given strategy and, hence, to evaluate different schemes of actions. Simulation is particularly relevant in very large systems where the statistical model...

The idea of combining discrete-event simulation and system dynamics has been a topic of debate in the operations research community for over a decade. Many authors have considered the potential benefits of such an approach from a methodological or practical standpoint. However, despite numerous...

We compare official population projections with Bayesian time series forecasts for England and Wales. The Bayesian approach allows the integration of uncertainty in the data, models and model parameters in a coherent and consistent manner. Bayesian methodology for time-series forecasting is...

Game theory is the science of strategic decision-making. It is a powerful tool in understanding the relationships that are made and broken in the course of competition and cooperation. It is not a panacea for the shortcomings of bad management. For managers, or those who interact with...