We estimate and compare two models, the Generalized Taylor Economy (GTE) and the Multiple Calvo model (MC), that have been built to model the distributions of contract lengths observed in the data. We compare the performances of these models to those of the standard models such as the Calvo and its popular variant, using the ad hoc device of indexation. The estimations are made with Bayesian te...

This note describes generalized expectation (GE) criteria, a framework for incorporating preferences about model expectations into parameter estimation objective functions. We discuss relations to other methods, various learning paradigms it supports, and applications that can leverage its flexibility.

The research in this paper was motivated by one of the most important open problems in the theory of generalized polygons, namely the existence problem for semi-finite thick generalized polygons. We show here that no semi-finite generalized hexagon of order (2, t) can have a subhexagon H of order 2. Such a subhexagon is necessarily isomorphic to the split Cayley generalized hexagon H(2) or its ...

Citations are increasingly used for research evaluations. It is therefore important to identify factors affecting citation scores that are unrelated to scholarly quality or usefulness so that these can be taken into account. Regression is the most powerful statistical technique to identify these factors and hence it is important to identify the best regression strategy for citation data. Citati...

This paper will discuss the basic principles underlying the theory of generalized linear models and the advantages of using generalized linear models over more traditional methods of actuarial modeling. Generalized linear models offer the flexibility needed to model real world data that does not conform to the strict assumptions underlying these traditional methods. The second part ofthis paper...