Results 61 to 70 of about 1,345 (165)
ABSTRACT We consider the problem of sequential (online) estimation of a single change point in a piecewise linear regression model under a Gaussian setup. We demonstrate that certain CUSUM‐type statistics attain the minimax optimal rates for localizing the change point.
Annika Hüselitz, Housen Li, Axel Munk
wiley +1 more source
Stability conditions for a Piecewise Deterministic Markov Process [PDF]
In the present paper we study the stability of a threshold continuos-time model that belongs to the class of Piecewise Deterministic Markov Processes. We derive a sufficient condition on the coefficients of the model to ensure the exponential ergodicity ...
Fonseca Giovanni
core
Causal Inference for Geostatistical Data Using an INLA‐based Spatial Propensity Score
ABSTRACT In this paper, we propose a Bayesian approach for spatial causal inference based on combining spatial propensity scoring with Integrated Nested Laplace Approximation. The method models both local and spillover exposure effects via multiple likelihoods and treats counterfactuals as missing data, allowing inference also for non‐Gaussian outcomes.
Chiara Di Maria +3 more
wiley +1 more source
Hybrid Reaction–Diffusion Epidemic Models: Dynamics and Emergence of Oscillations
ABSTRACT In this paper, we construct a hybrid epidemic mathematical model based on a reaction–diffusion system of the SIR (susceptible‐infected‐recovered) type. This model integrates the impact of random factors on the transmission rate of infectious diseases, represented by a probabilistic process acting at discrete time steps.
Asmae Tajani +2 more
wiley +1 more source
Optimal dividends for a NatCat insurer in the presence of a climate tipping point
Abstract We study optimal dividend strategies for an insurance company facing natural catastrophe claims, anticipating the arrival of a climate tipping point after which the claim intensity and/or the claim size distribution of the underlying risks deteriorates irreversibly.
Hansjörg Albrecher +2 more
wiley +1 more source
Cores for Piecewise-Deterministic Markov Processes used in Markov Chain Monte Carlo
We show fundamental properties of the Markov semigroup of recently proposed MCMC algorithms based on Piecewise-deterministic Markov processes (PDMPs) such as the Bouncy Particle Sampler, the Zig-Zag process or the Randomized Hamiltonian Monte Carlo ...
Holderrieth, Peter
core +1 more source
Analysis Of Upwind Method For Piecewise Deterministic Markov Processes [PDF]
AbstractA numerical upscaling approach, NU, for solving multiscale elliptic problems is discussed. The main components of this NU are: i) local solve of aux-iliary problems in grid blocks and formal upscaling of the obtained results to build a coarse scale equation; ii) global solve of the upscaled coarse scale equation; and iii) reconstruction of a ...
openaire +3 more sources
Robust estimation for Markov chains with applications to Piecewise-deterministic Markov Processes,
International audiencePiecewise-deterministic Markov processes form a class of stochastic models with a sizeable scope of applications: biology, insurance, neuroscience, networks, finance... Such processes are defined by a deterministic motion punctuated
Tillier, Charles +2 more
core
In this paper we introduce CPDPs (Communicating Piecewise Deterministic Markov Processes) as an automata formalism for compositional specification of hybrid systems of the type PDP.
S. N. Strubbe +3 more
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Eyring-Kramers type formulas for some piecewise deterministic Markov processes
In this work, we give sharp asymptotic equivalents in the small temperature regime of the smallest eigenvalues of the generator of some piecewise deterministic Markov processes (including the ZigZag process and the Bouncy Particle Sampler process) with ...
Le Peutrec, Dorian +2 more
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