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Leonidas Kordalis

Publications and source records attributed to Leonidas Kordalis.

3 recordsLinked to original sources

Multi-time Markov renewal chains and stratified renewal theorems

We develop a discrete Markov renewal theory on a standard Borel state space, with vector-valued sojourn times and lower-rectangle observation on $\N^d$. The Markov renewal potential is a kernel-valued convolution resolvent and yields unified representations for semi-Markov transitions, first-passage laws, occupation measures and rewards. The semi-Markov field observed on the partially ordered lattice is generally not Markov. We identify its canonical Markovian augmentation through the backward recurrence vector and give a lumpability criterion for the exceptional cases in which the augmentation can be projected back to the original state space. The lower-rectangle order leads to a stratified inverse-renewal theory: the direction simplex is decomposed into rate-determining cells, with Gaussian limits on cells having a unique active coordinate and minima of correlated Gaussian fields on their interfaces. We establish functional inverse limits, critical-interface limits and logarithmic estimates for inverse deviations. Exact-time potentials are obtained from an operator-theoretic local theorem for Fourier--Laplace perturbations of Markov-additive kernels, while a regenerative theorem gives the corresponding arithmetic lattice-class form. The results connect Markov renewal equations, multiparameter Markov structure and the local asymptotic geometry induced by rectangular observation.

math.PR

Discrete time-multidimensional renewal theory and applications

We develop a discrete-time renewal framework in which renewal events evolve along multiple time coordinates and the sojourn mechanism is described by a general distribution on the multi-index lattice. The resulting processes, called multi-time renewal chains, are studied through multi-index convolution and the associated algebra of multivariate formal power series. This algebraic formulation gives explicit representations for multi-time renewal equations, constructive coefficient formulas, and practical inversion schemes. For computation, we combine FFT-based multidimensional convolution with Newton-type reciprocal iteration to evaluate renewal quantities on large grids. For asymptotics, we prove strong laws and central limit theorems under proportional growth of the observation horizon, including a general central limit theorem for additive functionals and a Gaussian limit for the renewal counting process in directions with a unique rate-determining coordinate. We also study fixed-horizon observations: the terminal age vector induces a genuinely multivariate right-censoring mechanism, leading to an exact nonparametric maximum likelihood estimator and its asymptotic normality. Applications include a binomial--multiset identity, two-attribute warranty evaluation, alternating-renewal availability computation, and discretization-based approximations of continuous-time bivariate renewal and availability models.

math.PR

Time multidimensional Markov Renewal chains -- An algebraic approach

In this study, a new extension of the Markov Renewal theory is introduced by allowing time to evolve in multiple dimensions. The resulting chains are referred to as multi-time Markov Renewal chains and since this extension is new, the state space is assumed to be finite to cover the theoretical framework of applications, where the possible number of states of a physical system is finite. The flexibility of Markov renewal theory is still present in multiple time dimensions by allowing the sojourn times in the different states of the system to be arbitrarily selected from a multidimensional distribution. The convolution product of multidimensional matrix sequences plays a particular role in the development of the theory and some of its algebraic properties are given and explored, paying particular attention to the existence, the representation and the computation of the convolutional inverse. Some basic definitions and properties of this new class are given as well as the multi-time Markov renewal equations associated to the resulting processes. The practical implementation is achieved very efficiently through a novel adaptation of the Gauss-Jordan algorithm for multidimensional matrix sequences.

math.PR