2 citations · 4 across the 11 of their papers we have counts for
7 papers · 1 filter
Allowing for imprecision in the game-theoretic characterisation of the Poisson process
Alexander Erreygers
In their 1993 paper 'Forecasting point and continuous processes: Prequential analysis' in Test, Vovk put forward a game-theoretic definition of the Poisson process. A key assumptio…
A convenient characterisation of convergent upper transition operators
Jasper De Bock, Alexander Erreygers, Floris Persiau
Motivated by its connection to the limit behaviour of imprecise Markov chains, we introduce and study the so-called convergence of upper transition operators: the condition that fo…
Countable-state stochastic processes with càdlàg sample paths
Alexander Erreygers, Jasper De Bock
The Daniell-Kolmogorov Extension Theorem is a fundamental result in the theory of stochastic processes, as it allows one to construct a stochastic process with prescribed finite-di…
Sublinear expectations for countable-state uncertain processes
Alexander Erreygers
Sublinear expectations for uncertain processes have received a lot of attention recently, particularly methods to extend a downward-continuous sublinear expectation on the bounded…
First Steps Towards an Imprecise Poisson Process
Alexander Erreygers, Jasper De Bock
The Poisson process is the most elementary continuous-time stochastic process that models a stream of repeating events. It is uniquely characterised by a single parameter called th…
Computing Inferences for Large-Scale Continuous-Time Markov Chains by Combining Lumping with Imprecision
Alexander Erreygers, Jasper De Bock
If the state space of a homogeneous continuous-time Markov chain is too large, making inferences - here limited to determining marginal or limit expectations - becomes computationa…
Imprecise Continuous-Time Markov Chains: Efficient Computational Methods with Guaranteed Error Bounds
Alexander Erreygers, Jasper De Bock
Imprecise continuous-time Markov chains are a robust type of continuous-time Markov chains that allow for partially specified time-dependent parameters. Computing inferences for th…