The choice of the summary statistics in Bayesian inference and in particular in ABC algorithms is paramount to produce a valid outcome. We derive necessary and sufficient conditions on those statistics for the corresponding Bayes factor to be convergent, namely to asymptotically select the true...

In practice, parametric likelihood-ratio techniques are powerful statistical tools. In this article, we propose and examine novel and simple distribution-free test statistics that efficiently approximate parametric likelihood ratios to analyze and compare distributions of K groups of...

This paper proposes a swarm intelligence approach based on a disjunctive graph model in order to schedule a manufacturing system with resource flexibility and separable setup times. Resource flexibility assigns each operation to one of the alternative resources (assigning sub-problem) and,...

In this paper, we analyze a game called the lowest unique bid auction (LUBA). It is known that there is no closed form solution for the symmetric mixed strategy equilibria in LUBA. We propose two alternative approaches. We use weak dominance to identify upper bounds for players’ bids. Under...

Three computational techniques for approximation of counterparty exposure for financial derivatives are presented. The exposure can be used to quantify so-called Credit Valuation Adjustment (CVA) and Potential Future Exposure (PFE), which are of utmost importance for modern risk management in...

A novel hybrid evolutionary algorithm is developed based on the particle swarm optimization (PSO) and genetic algorithms (GAs). The PSO phase involves the enhancement of worst solutions by using the global-local best inertia weight and acceleration coefficients to increase the efficiency. In the...