In this paper we propose two exact algorithms for solving both two-staged and three-staged unconstrained (un) weighted cutting problems. The two-staged problem is solved by applying a dynamic programming procedure originally developed by Gilmore and Gomory [10]. The three-staged problem is...

This paper combines two estimation procedures: Iterative Generalized Least Squares as used in the sofware MLwiN; Gibbs Sampling as employed in the software BUGS to Produce a modelling strategy that respects the hierachical nature of the Teaching Styles data and also allows for the endogeneity...

This paper prouves a new representation theorem for domains with both discrete and continuous variables.

As part of a study aimed at estimating suburban highway needs for year 2005, models were developed for forecasting daily vehicle miles of travel (DVMT) for urban areas and its distribution by highway functional class, urban location, and urban area size. A regression model combining both time...

In this paper we present a meta-heuristic, known as a genetic algorithm, in order to solve the problems of (weigthed) independent set (IS), vertex covering (VC), set packing (SP) and maximum clique (MC).

We propose a test for spatial correlation in Probit models that is a joint test for exclusion of spatially lagged-dependent variables and absence of spatial-error correlation. We give a maximum-likelihood justification for the test but use a simulations approach rather than relying on its...

This paper proposes alternative methods for constructing estimators from accept-reject samples by incorporating the variables rejected by the algorithm.

This paper synthesises a global approach to both Bayesian and likelihood treatments of the estimation of the parameters of a hidden Markov model for the cases of normal and Poisson underlying distribution.