Knowledge flows and the geography of networks. A strategic model of small worlds formation.

This paper aims to demonstrate that the strategic approach of network formation can generate networks that share the main structural properties of most real social networks. We introduce a spatialized variation of the Connections model (Jackson and Wolinski, 1996) in which agents balance the benefits of forming links resulting from imperfect knowledge flows through bonds against their costs which increase with geographic distance. We show that, for intermediary levels of knowledge transferability, our time-inhomogeneous process selects networks which exhibit high clustering, short average distances and, when the costs of link formation are normally distributed across agents, skewed degree distributions.Strategic network formation ; Time-inhomogeneous process ; Knowledge flows ; Small worlds ; Monte Carlo simulations.

DFTCalc: a tool for efficient fault tree analysis (extended version)

Effective risk management is a key to ensure that our nuclear power plants, medical equipment, and power grids are dependable; and is often required by law. Fault Tree Analysis (FTA) is a widely used methodology here, computing important dependability measures like system reliability. This paper presents DFTCalc, a powerful tool for FTA, providing (1) efficient fault tree modelling via compact representations; (2) effective analysis, allowing a wide range of dependability properties to be analysed (3) efficient analysis, via state-of-the-art stochastic techniques; and (4) a flexible and extensible framework, where gates can easily be changed or added. Technically, DFTCalc is realised via stochastic model checking, an innovative technique offering a wide plethora of pow- erful analysis techniques, including aggressive compression techniques to keep the underlying state space small

Forgalom modellezési módszerek fejlesztése = Advanced traffic modeling techniques

A projekt alapvetően sikeresen járult hozzá a vizsgált szakterület eredményeinek bővítéséhez és a résztvevő kutatócsoport fejlődéséhez. A projekt eredményihez kapcsolódó dolgozatok alapján PHD fokozatot szerzett Bodrog Levente és Saffer Zsolt. A projekt eredményeit összegző publikációk együttes impakt faktora ~22. A szakmai eredmenyek közül Markov érkezési folyamatok alapvető tulajdonságait összegző cikk (A minimal representation of Markov arrival processes and a moments matching method) emelhető ki, amelyik időközben az ezen folyamatok illesztési korlátait vizsgálló munkák alapjává vált. | The project successfully enhanced the field of traffic modeling of computer and communication systems and helped to improve the carrier of the involved research group. Based on the their theses summarizing parts of the results of the project Bodrog Levente and Saffer Zsolt were awarded the doctor of philosophy degree. The cumulated impact factor of the journal papers publish the research results of the project is about 22. The most remarkable research results are in the paper summarizing some basic properties of Markov arrival processes (A minimal representation of Markov arrival processes and a moments matching method), which become a basic reference for subsequent works dealing with the fitting properties of these processes

Knowledge flows and the geography of networks: a strategic model of small world formation

"This paper aims to demonstrate that the strategic approach to link formation can generate networks that share some of the main structural properties of most real social networks. For this purpose, we introduce a spatialized variation of the Connections model (Jackson and Wolinsky 1996) to describe the strategic formation of links by agents who balance the benefits of forming links resulting from imperfect knowledge flows against their costs, which increase with geographic distance. We show, for intermediate levels of knowledge transferability, clustering occurs in geographical space and a few agents sustain distant connections. Such networks exhibit the small world property (high clustering and short average relational distances). When the costs of link formation are normally distributed across agents, asymmetric degree distributions are also obtained." [author's abstract

Multivariate Stochastic Volatility Models: Bayesian Estimation and Model Comparison

In this paper we show that fully likelihood-based estimation and comparison of multivariate stochastic volatility (SV) models can be easily performed via a freely available Bayesian software called WinBUGS. Moreover, we introduce to the literature several new specifications which are natural extensions to certain existing models, one of which allows for time varying correlation coefficients. Ideas are illustrated by fitting, to a bivariate time series data of weekly exchange rates, nine multivariate SV models, including the specifications with Granger causality in volatility, time varying correlations, heavytailed error distributions, additive factor structure, and multiplicative factor structure. Empirical results suggest that the most adequate specifications are those that allow for time varying correlation coefficients.Multivariate stochastic volatility; Granger causality in volatility; Heavy-tailed distributions; Time varying correlations; Factors; MCMC; DIC.

On the Properties of Moments of Matrix Exponential Distributions and Matrix Exponential Processes

In this paper we provide properties of moments of matrix exponential distributions and joint moments of matrix exponential processes. Based on the provided properties, an algorithm is presented to compute any finite dimensional moments of these processes based on a set of required (low order) moments. This algorithm does not require the computation of any representation of the given process. We present some related examples to demonstrate the potential use of the properties of moments

Complex networks analysis in socioeconomic models

This chapter aims at reviewing complex networks models and methods that were either developed for or applied to socioeconomic issues, and pertinent to the theme of New Economic Geography. After an introduction to the foundations of the field of complex networks, the present summary adds insights on the statistical mechanical approach, and on the most relevant computational aspects for the treatment of these systems. As the most frequently used model for interacting agent-based systems, a brief description of the statistical mechanics of the classical Ising model on regular lattices, together with recent extensions of the same model on small-world Watts-Strogatz and scale-free Albert-Barabasi complex networks is included. Other sections of the chapter are devoted to applications of complex networks to economics, finance, spreading of innovations, and regional trade and developments. The chapter also reviews results involving applications of complex networks to other relevant socioeconomic issues, including results for opinion and citation networks. Finally, some avenues for future research are introduced before summarizing the main conclusions of the chapter.Comment: 39 pages, 185 references, (not final version of) a chapter prepared for Complexity and Geographical Economics - Topics and Tools, P. Commendatore, S.S. Kayam and I. Kubin Eds. (Springer, to be published