In this paper time series identification problem amounts to estimating the unknown parameters of an ARMA model, which is transformed to an infinite AR model. A modification of the Least Squares method is proposed for the identification of an AR model of infinite order. The analysis of convergence of the LS estimates with probability 1 is carried out for an infinite case. Moreover, it is establi...

This note describes a method for approximate inference in infinite models that uses deterministic Expectation Propagation instead of Monte Carlo. For infinite Gaussian mixtures, the algorithm provides cluster parameter estimates, cluster memberships, and model evidence. Model parameters, such as the expected size of the mixture, can be efficiently tuned via EM with EP as the E-step. The same ap...

We study a constrained percolation process on Z, and prove the almost sure nonexistence of infinite clusters and contours for a large class of probability measures. Unlike the unconstrained case, in the constrained case no stochastic monotonicity is known. We prove the nonexistence of infinite clusters and contours for the constrained percolation by developing new combinatorial techniques which...

Molchan-Golosov fractional Lévy processes (MG-fLps) are introduced by a multivariate componentwise Molchan-Golosov transformation based on an n-dimensional driving Lévy process. Using results of fractional calculus and infinitely divisible distributions we are able to calculate the conditional characteristic function of integrals driven by MG-fLps. This leads to important prediction results inc...

We consider the problem of allocating an amount of a perfectly divisible good among a group of n agents. We study how large a preference domain can be to allow for the existence of strategy-proof, symmetric, and efficient allocation rules when the amount of the good is a variable. This question is qualified by an additional requirement that a domain should include a minimally rich domain. We fi...

The possibility to identify linear systems from finite data, e.g. a partial impulse response, is determined by the degree of corroboration of system restrictions by the observed data. Ala~'Kt-In this paper we investigate the identification of systems from time series observed over a finite time interval. The data generating system is supposed to be finite dimensional, linear and time invariant,...

We describe computational modeling of flaring horns and piecewise conical bores using “Truncated Infinite Impulse Response” (TIIR) digital filtering techniques. The approach yields highly efficient and accurate computational models and is therefore appropriate for real-time simulations of woodwind and brass musical instruments.

This study discusses some variants of Ordered WeightedAveraging (OWA) operators and related information aggregation methods. Indetail, we define the Extended Ordered Weighted Sum (EOWS) operator and theExtended Ordered Weighted Averaging (EOWA) operator, which are applied inscientometrics evaluation where the preference is over finitely manyrepresentative works. As...

We propose a semi-discrete in time semi-implicit numerical scheme for the infinite Prandtl model for convection. Besides the usual finite time convergence, this scheme enjoys the additional highly desirable feature that the stationary statistical properties of the scheme converge to those of the infinite Prandtl number model at vanishing time step. One of the key characteristics of the scheme i...

We construct a random matrix model for the bijection Ψ between classical and free infinitely divisible distributions: for every d ≥ 1, we associate in a quite natural way to each ∗-infinitely divisible distribution μ a distribution Pμd on the space of d×d hermitian matrices such that Pμd ∗ Pνd = P μ∗ν d . The spectral distribution of a random matrix with distribution Pμd converges in probabilit...