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Marginal-likelihood based model-selection, even though promising, is rarely used in deep learning due to estimation difficulties. Instead, most approaches rely on validation data, which may not be readily available. In this work, we present…

Machine Learning · Statistics 2021-06-16 Alexander Immer , Matthias Bauer , Vincent Fortuin , Gunnar Rätsch , Mohammad Emtiyaz Khan

The typical central limit theorems in high-frequency asymptotics for semimartingales are results on stable convergence to a mixed normal limit with an unknown conditional variance. Estimating this conditional variance usually is a hard…

Probability · Mathematics 2020-03-25 Mathias Vetter

Symbolic transfer entropy is a powerful non-parametric tool to detect lead-lag between time series. Because a closed expression of the distribution of Transfer Entropy is not known for finite-size samples, statistical testing is often…

Statistical Finance · Quantitative Finance 2022-06-22 Christian Bongiorno , Damien Challet

This paper presents a simulation study on turnpike phenomena in stochastic optimal control problems. We employ the framework of Polynomial Chaos Expansions (PCE) to investigate the presence of turnpikes in stochastic LQ problems. Our…

Systems and Control · Electrical Eng. & Systems 2020-10-26 Ruchuan Ou , Michael Heinrich Baumann , Lars Grüne , Timm Faulwasser

We provide asymptotic results and develop high frequency statistical procedures for time-changed L\'evy processes sampled at random instants. The sampling times are given by first hitting times of symmetric barriers whose distance with…

Probability · Mathematics 2010-07-20 Mathieu Rosenbaum , Peter Tankov

We develop an approach to learn an interpretable semi-parametric model of a latent continuous-time stochastic dynamical system, assuming noisy high-dimensional outputs sampled at uneven times. The dynamics are described by a nonlinear…

Machine Learning · Statistics 2019-02-13 Lea Duncker , Gergo Bohner , Julien Boussard , Maneesh Sahani

Many stochastic physical systems evolve smoothly over time in the sense that the distribution of states changes regularly across time steps. The transition from current state to the next state can often be modeled as the combination of a…

Machine Learning · Computer Science 2026-05-29 Jules Berman , Tobias Blickhan , Benjamin Peherstorfer

We consider the lattice dynamics in the half-space. The initial data are random according to a probability measure which enforces slow spatial variation on the linear scale $\varepsilon^{-1}$. We establish two time regimes. For times of…

Mathematical Physics · Physics 2015-05-13 T. V. Dudnikova

We determine the operator limit for large powers of random tridiagonal matrices as the size of the matrix grows. The result provides a novel expression in terms of functionals of Brownian motions for the Laplace transform of the…

Probability · Mathematics 2016-01-27 Vadim Gorin , Mykhaylo Shkolnikov

We investigate the first-passage properties of a jump process with a constant drift, focusing on two key observables: the first-passage time $\tau$ and the number of jumps $n$ before the first-passage event. By mapping the problem onto an…

Statistical Mechanics · Physics 2025-07-31 Ivan N. Burenev , Satya N. Majumdar

In this paper we present some limit theorems for power variation of L\'evy semi-stationary processes in the setting of infill asymptotics. L\'evy semi-stationary processes, which are a one-dimensional analogue of ambit fields, are moving…

Probability · Mathematics 2016-10-17 Andreas Basse-O'Connor , Claudio Heinrich , Mark Podolskij

This paper presents a nonparametric method for estimating the conditional density associated to the jump rate of a piecewise-deterministic Markov process. In our framework, the estimation needs only one observation of the process within a…

Statistics Theory · Mathematics 2012-07-12 Romain Azaïs , François Dufour , Anne Gégout-Petit

We propose automated techniques for the verification and control of probabilistic real-time systems that are only partially observable. To formally model such systems, we define an extension of probabilistic timed automata in which local…

Logic in Computer Science · Computer Science 2015-06-24 Gethin Norman , David Parker , Xueyi Zou

In this article, we introduce Mittag-Leffler L\'evy process and provide two alternative representations of this process. First, in terms of Laplace transform of the marginal densities and next as a subordinated stochastic process. Both…

Probability · Mathematics 2016-02-05 Arun Kumar , N. S. Upadhye

This paper studies the long-time behavior of optimal solutions for a class of linear-convex optimal control problems. We focus on a partial exponential turnpike property, established without imposing controllability or stabilizability…

Optimization and Control · Mathematics 2026-02-10 Jingrui Sun , Lvning Yuan

Consider the sum $Y=B+B(H)$ of a Brownian motion $B$ and an independent fractional Brownian motion $B(H)$ with Hurst parameter $H\in(0,1)$. Even though $B(H)$ is not a semimartingale, it was shown in [\textit{Bernoulli} \textbf{7} (2001)…

Statistics Theory · Mathematics 2024-10-28 Carsten H. Chong , Thomas Delerue , Fabian Mies

The L\'evy walk process with rests is discussed. The jumping time is governed by an $\alpha$-stable distribution with $\alpha>1$ while a waiting time distribution is Poissonian and involves a position-dependent rate which reflects a…

Statistical Mechanics · Physics 2017-10-11 A. Kamińska , T. Srokowski

This paper proposes novel tests for the absence of jumps in a univariate semimartingale and for the absence of common jumps in a bivariate semimartingale. Our methods rely on ratio statistics of power variations based on irregular…

Statistics Theory · Mathematics 2017-12-21 Ole Martin , Mathias Vetter

Advances in experimental techniques allow the collection of high-resolution spatio-temporal data that track individual motile entities over time. These tracking data motivate the use of mathematical models to characterise the motion…

Data Analysis, Statistics and Probability · Physics 2025-03-30 Arianna Ceccarelli , Alexander P. Browning , Ruth E. Baker

We construct an aggregated version of the value processes associated with stochastic control problems, where the criterion to optimise is given by solutions to semi-martingale backward stochastic differential equations (BSDEs). The results…

Probability · Mathematics 2025-07-03 Dylan Possamaï , Marco Rodrigues , Alexandros Saplaouras