Ricerc@Sapienza

Given a (finitely additive) full conditional probability space and a conditional measurable space , a multivalued mapping Γ from X to Y induces a class of full conditional probabilities on . A closed form expression for the lower and upper envelopes ⁎ and ⁎ of such class is provided: the envelopes can be expressed through a generalized Bayesian conditioning rule, relying on two linearly ordered classes of (possibly unbounded) inner and outer measures.

In official statistics, interest for data integration has been increasingly growing, due to the need of extracting information from different sources. However, the effects of these procedures on the validity of the resulting statistical analyses has been disregarded for a long time. In recent years, it has been largely recognized that linkage is not an error-free procedure and linkage errors, as false links and/or missed links, can invalidate the reliability of estimates in standard statistical models.

The dynamics of a nonlinearly coupled electro-magneto-mechanical system is numerically investigated with the aim to obtain a comprehensive description of its behavior in strongly nonlinear regime. Bifurcation diagrams and stability charts as a function of the main system parameters allow to detect several multistable and unstable regions, characterized by coexistence of low-amplitude and high-amplitude responses, and by the presence of wide ranges of chaotic motions, which have been connoted by computing the relevant Lyapunov characteristic exponents.

Nafion membranes, are polymeric thin films widely employed in micro-batteries and fuel cells. These devices are expected to play a key role in the next generation energy systems for use in vehicles as a replacement to combustion engines. In fact, a minimum environmental impact is guaranteed by reduced carbon dioxide emissions. It is usually complicated to investigate the behavior of thin membranes through experiments. Therefore, numerical simulations are carried out in order to enable a better understanding of the phenomena and of the multi-field couplings occurring in polymeric membranes.

This paper includes a twofold result for the Nonlinear Conjugate Gradient (NCG) method, in large scale unconstrained optimization. First we consider a theoretical analysis, where preconditioning is embedded in a strong convergence framework of an NCG method from the literature. Mild conditions to be satisfied by the preconditioners are defined, in order to preserve NCG convergence. As a second task, we also detail the use of novel matrix-free preconditioners for NCG.

In this paper, we consider the problem of disturbance decoupling for a class of non-minimum-phase nonlinear systems. Based on the notion of partially minimum phaseness, we shall characterize all actions of disturbances which can be decoupled via a static state feedback while preserving stability of the internal residual dynamics. The proposed methodology is then extended to the sampled-data framework via multi-rate design to cope with the rising of the so-called sampling zero dynamics intrinsically induced by classical single-rate sampling.

Undirected Vertex Geography (UVG) is an impartial two-person game played on a (undirected) graph G with a specified vertex u. Players, Alice and Bob, alternately choose a vertex that has not been chosen before and that is adjacent to the last chosen vertex. Alice plays first, choosing an adjacent vertex of u. The first player who is unable to choose a vertex loses. Determining whether Alice has a winning strategy in this game (the UVG problem) is known to be solvable in polynomial time.

This special issue of the International Journal of Approximate Reasoning (IJAR) focuses on recent advances in soft methods in probability and statistics.The special issue is a follow-up of the 8th International Conference on Soft Methods in Probability and Statistics (SMPS2016),which took place in Rome (Italy) in September 2016 (http://www.sbai.uniroma1.it/smps2016/index.php).

We deal with some extensions of the space-fractional diffusion equation, which is satisfied by the density
of a stable process (see Mainardi et al. (2001)): the first equation considered here is obtained by adding an
exponential differential (or shift) operator expressed in terms of the Riesz–Feller derivative. We prove that
this produces a random component in the time-argument of the corresponding stable process, which is
represented by the so-called Poisson process with drift. Analogously, if we add, to the space-fractional

The detection of patterns in multivariate time series is a relevant task, especially for large datasets. In this paper, four clustering models for multivariate time series are proposed, with the following characteristics. First, the Partitioning Around Medoids (PAM) framework is considered. Among the different approaches to the clustering of multivariate time series, the observation-based is adopted. To cope with the complexity of the features of each multivariate time series and the associated assignment uncertainty a fuzzy clustering approach is adopted.