In this paper we consider statistical distributions of different types of patients on the patient lists of doctors. In our framework different types of patients have different preferences regarding their preferred choice of doctor. Assuming that the system is benefit efficient in the sense that...

In this paper we will show how the patient list model in Uboslash;e amp; Lillestoslash;l (2007) can be used to infer strength of preferences from patient list data. We prove that we can construct unique sets of preferences that replicates patient list data, and we also show how to approach cases...

Time series models for count data have found increased interest in recent days. The existing literature refers to the case of data that have been fully observed. In the present paper, methods for estimating the parameters of the first-order integer-valued autoregressive model in the presence of...

In this paper, we propose a likelihood ratio and Markov chain based method to evaluate density forecasting. This method can jointly evaluate the unconditional forecasted distribution and dependence of the outcomes. This method is an extension of the widely applied evaluation method for interval...