Logarithmic law of large random correlation matrices

Consider a random vector y = Σ ^1/2 x, where the p elements of the vector x are i.i.d. real-valued random variables with zero mean and finite fourth moment, and Σ ^1/2 is a deterministic p × p matrix such that the eigenvalues of the population correlation matrix R of y are uniformly bounded away from zero and infinity. In...

Regular vines with strongly chordal pattern of (conditional) independence

Multivariate statistical models can be simplified by assuming that a pattern of conditional independence is presented in the given data. A popular way of capturing the (conditional) independence is to use probabilistic graphical models. The relationship between strongly chordal graphs and m-saturated vines is proved. Moreover, an algorithm to...

Selecting technologies in aircraft conceptual design using probabilistic inversion

Technology forecasting is an essential starting point for conceptual design of any complex engineering system. In fact, many research projects are focused on developing a small set of promising technologies to a suitable readiness level. However, selecting a set of technologies from a larger pool is a nontrivial task, opposed by uncertainty...

The Eco-Costs of Material Scarcity, a Resource Indicator for LCA, Derived from a Statistical Analysis on Excessive Price Peaks

The availability of resources is crucial for the socio-economic stability of our society. For more than two decades, there was a debate on how to structure this issue within the context of life-Cycle assessment (LCA). The classical approach with LCA is to describe "scarcity" for future generations (100-1000 years) in terms of absolute...

A copula-based sensitivity analysis method and its application to a North Sea sediment transport model

This paper describes a novel sensitivity analysis method, able to handle dependency relationships between model parameters. The starting point is the popular Morris (1991) algorithm, which was initially devised under the assumption of parameter independence. This important limitation is tackled by allowing the user to incorporate dependency...

Impact of railway disruption predictions and rescheduling on passenger delays

Disruptions such as rolling stock breakdown, signal failures, and accidents are recurrent events during daily railway operation. Such events disrupt the deployment of resources and cause delay to passengers. Obtaining a reliable disruption length estimation can potentially reduce the negative impact caused by the disruption. Different factors...

The Copula Bayesian Network with mixed discrete and continuous nodes to forecast railway disruption lengths

The highly uncertain nature of a railway disruption complicates the tasks carried by the Dutch Operational Control Centre Rail (OCCR) in the Netherlands. A good prediction of disruption length is believed to help the decision making in dealing with the disruption. Zilko, et al. [Non-Parametric Bayesian Network to Forecast Railway Disruption...

About the number of vines and regular vines on n nodes

The theory of graphs is important not only for combinatorial problems but in physics, electrical engineering, chemistry, social psychology, and research of operations. Labeled trees find application in probability theory. These objects were first successfully counted by Cayley in 1889. Vines generalize trees. They were introduced by Cooke in...

Prioritizing Emerging Zoonoses in The Netherlands

Background: To support the development of early warning and surveillance systems of emerging zoonoses, we present a general method to prioritize pathogens using a quantitative, stochastic multi-criteria model, parameterized for the Netherlands. Methodology/Principal Findings: A risk score was based on seven criteria, reflecting assessments of...

Using copulas for modeling stochastic dependence in power system uncertainty analysis

The increasing penetration of renewable generation in power systems necessitates the modeling of this stochastic system infeed in operation and planning studies. The system analysis leads to multivariate uncertainty analysis problems, involving non-Normal correlated random variables. In this context, the modeling of stochastic dependence is...

Attribution of Foodborne Pathogens Using Structured Expert Elicitation

Objectives: To estimate the fraction of human cases of enterically transmitted illness by five major pathways (food, environment, direct animal contact, human–human transmission, and travel) and by 11 groups within the food pathway. Methods: Food safety experts were asked to provide their estimates of the most likely range for each of the...

Causal Model for Air Transport Safety: Final report

Continuous/discrete non parametric Bayesian belief nets with UNICORN and UNINET

Hanea et al. (2006) presented a method for quantifying and computing continuous/discrete non parametric Bayesian Belief Nets (BBN). Influences are represented as conditional rank correlations, and the joint normal copula enables rapid sampling and conditionalization. Further mathematical background is in Kurowicka and Cooke (2007). This article...

Techniques in Representing High Dimensional Distributions