Syntactic structures have been analysed in terms of constituent hierarchies and also in terms of dependency relations. While these two traditions have sometimes been presented as competing with each other, there is no reason in principle why syntactic dependencies and constituent hierarchies should not both be part of the grammar, complementing each other. Indeed, within transformational gramma...

We present a methodology for the non-linear analysis of long-term ecological time series. Using a time-delay embedding procedure, we investigated the complexity of 1-dimensional signals and compared their structure to their stochastic counterparts. Recurrence-based statistics and surrogate testing were used for this purpose. The method was first tested on elementary models for illustrative purp...

We study the value of the mean entropy production as a function of the level of description. We prove that by coarsening the system, we obtain a lower entropy production. As main example we consider the Lorentz lattice gas and prove that the microscopic entropy production is strictly larger than the one predicted by the Boltzmann equation.

In this paper we prove that a uniformly distributed random circular automaton A n of order synchronizes with high probability (w.h.p.). More precisely, P [ ] = 1 − O ( ) . The main idea the proof is to translate synchronization problem into concerning properties matrix; these are then established by careful analysis stochastic dependence structure among entries matrix. Additionally, provide an ...

We introduce the concept of ordinal pattern dependence between time series and show in an explorative study that both types of this dependence show up in real world nancial data. The classical way to capture the leverage e ect in models for stock markets is to assume a negative correlation between the two datasets which is constant in time (e.g. Barndor Nielsen and Shepard (2002)). However, the...

Given a collection of random variables i ] i2N where N is a nite nonempty set, the corresponding multiinformation function ascribes the relative entropy of the joint distribution of i ] i2A with respect to the product of distributions of individual random variables i for i 2 A to every subset A N. We argue it is a useful tool for problems concerning stochastic (conditional) dependence and indep...

ii I certify that I have read this dissertation and certify that in my opinion it is fully adequate, in scope and in quality, as a dissertation for the degree of Doctor of Philosophy. Stochastic dependence arises in many fields including electrical grid reliability, net-work/internet traffic analysis, environmental and agricultural impact assessment, and financial risk management. Models in the...

We study stochastic differential equations (SDEs) whose drift and diffusion coefficients are path-dependent and controlled. We construct a value process on the canonical path space, considered simultaneously under a family of singular measures, rather than the usual family of processes indexed by the controls. This value process is characterized by a second order backward SDE, which can be seen...

Maximum autoregressive processes like MARMA (Davis and Resnick, [5] 1989) or power MARMA (Ferreira and Canto e Castro, [12] 2008) have singular joint distributions, an unrealistic feature in most applications. To overcome this pitfall, absolute continuous versions were presented in Alpuim and Athayde [2] (1990) and Ferreira and Canto e Castro [14] (2010b), respectively. We consider an extended ...

ion methods for dimensionality-reduction Abstractions methods are used to complement iterative algorithms for computing equilibria. Abstractions are usually created algorithmically, by utilizing domain-dependent structure to set up a manageable optimization problem that produces a smaller game which retains as much of the original game structure as possible. No reasonable bounds on solution qua...