We study a stochastic multiplicative system composed of finite asynchronous elements to describe the wealth evolution in financial markets. We find that the wealth fluctuations or returns of this system can be described by a walk with correlated step sizes obeying truncated Lévy-like distribution, and the cross-correlation between relative updated wealths is the origin of the nontrivial propert...

This paper deals with the problem of estimating the probability that one event was a cause of another in a given scenario. Using structural-semantical deenitions of the probabilities of necessary or suucient cau-sation (or both), we show h o w to optimally bound these quantities from data obtained in experimental and observational studies, making minimal assumptions concerning the data-generati...

The causal states of computational mechanics define the minimal sufficient (prescient) memory for a given stationary stochastic process. They induce the ε-machine which is a hidden Markov model (HMM) generating the process. The ε-machine is, however, not the minimal generative HMM and minimal internal state entropy of a generative HMM is a tighter upper bound for excess entropy than provided by...

We study the flavour breaking effects appearing in the Wilson twisted mass formulation of lattice QCD. In this quenched study, we focus on the mass splitting between the neutral and the charged pion, determining the neutral pion mass with a stochastic noise method to evaluate the disconnected contributions. We find that these disconnected contributions are significant. Using the Osterwalder-Sei...

This paper introduces a generalized framework, termed “stochastic cloning,” for processing relative state measurements within a Kalman filter estimator. The main motivation and application for this methodology is the problem of fusing displacement measurements with position estimates for mobile robot localization. Previous approaches have ignored the developed interdependencies (cross-correlati...

Predictability is a measure of prediction error relative to observed variability and so depends on both the physical and prediction systems. Here predictability is investigated for climate phenomena described by linear stochastic dynamics and prediction systems with perfect initial conditions and perfect linear prediction dynamics. Predictability is quantified using the predictive information m...

Business process execution generates great amounts of information on process results and intermediate activities. Most of this information is represented by events linked to their related process execution. Process monitoring uses such events and links to correlate incoming events to their corresponding process instances. These links may however get lost in the process of event capturing or not...

Computer-assisted stratigraphic correlation can help to produce several scenarios reflecting interpretation uncertainties. In this work, we propose a method which translates sedimentary concepts into cost for each possible stratigaphic correlation. All these costs are used populate matrix in order apply the Dynamic Time Warping algorithm and compute n-best sets having n-least cumulative costs. ...