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S. Trevezas

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Preprint Jul 2026

Multi-time Markov renewal chains and stratified renewal theorems

We develop stratified renewal theorems for multi-time observations of Markov-additive paths on standard Borel state spaces with nonnegative integer vector increments. Horizon directions with the same active constraints form strata. A compact-uniform inverse expansion yields a global limit in a topology combining hypi-c...

Leonidas Kordalis, S. Trevezas · 0 citations
Preprint Sep 2026

Hermite Spectra and Kernel Factorization for Gaussian-Weighted Tests of Normality

We study the asymptotic null spectrum of Gaussian-weighted tests of univariate normality with estimated location and scale. Closed Hermite coefficients give equations both away from and at the unperturbed poles. Every positive eigenvalue of the fully standardized covariance is simple, and the odd and even eigenvalues a...

N. Gkoumas, N. Papadatos, S. Trevezas · 0 citations
Open access Jul 2026

Reliability Inference for Semi-Markov Models based on Multiple Trajectories

We develop nonparametric inference for reliability indicators of discrete-time semi-Markov systems from independent trajectories observed over a common fixed horizon. Augmenting the physical state by the backward recurrence time yields a finite coupled Markov representation on the observed age range. We distinguish the...

S. Trevezas, M. Hamdaoui, Irène Votsi · 0 citations
Preprint Jul 2026

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 me...

Leonidas Kordalis, Samis Trevezas · 0 citations
Preprint Jul 2026

Matrix asymptotic calculus for plug-in maximum likelihood estimators in finite Markov chains

A unified matrix-level asymptotic calculus for plug-in non-parametric maximum likelihood estimators in finite Markov models, where the stochastic constraints of the transition matrix need not be removed by a minimal parametrization.

G. Gavrilopoulos, S. Trevezas, Irène Votsi · 1 citation
Preprint Jul 2026

Evaluating the Impact of Epidemic Control via State-Dependent Markovian Switching Modeling

An exact finite-population stochastic framework for SIR epidemics evolving under Markovian switching between intervention regimes is developed, showing how switching mechanisms affect both the total number of infected individuals and the extinction time, including their dispersion.

Vasileios E. Papageorgiou, Irène Votsi, S. Trevezas · 0 citations

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