MARKOV PROCESSES CONDITIONED ON THEIR LOCATION AT LARGE EXPONENTIAL TIMES. [PDF]
Evans SN, Hening A.
europepmc +1 more source
A goodness‐of‐fit test for regression models with discrete outcomes
Abstract Regression models are often used to analyze discrete outcomes, but classical goodness‐of‐fit tests such as those based on the deviance or Pearson's statistic can be misleading or have little power in this context. To address this issue, we propose a new test, inspired by the work of Czado et al.
Lu Yang +2 more
wiley +1 more source
Algebraic formulas for first-passage times of Markov processes in the linear framework. [PDF]
Nam KM, Gunawardena J.
europepmc +1 more source
Efficient analysis of stochastic gene dynamics in the non-adiabatic regime using piecewise deterministic Markov processes. [PDF]
Lin YT, Buchler NE.
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Invariant Measure and Universality of the 2D Yang–Mills Langevin Dynamic
ABSTRACT We prove that the Yang–Mills (YM) measure for the trivial principal bundle over the two‐dimensional torus, with any connected, compact structure group, is invariant for the associated renormalised Langevin dynamic. Our argument relies on a combination of regularity structures, lattice gauge‐fixing and Bourgain's method for invariant measures ...
Ilya Chevyrev, Hao Shen
wiley +1 more source
Bounds on Fluctuations of First Passage Times for Counting Observables in Classical and Quantum Markov Processes. [PDF]
Bakewell-Smith G +3 more
europepmc +1 more source
Local Composite Quantile Regression Smoothing for Harris Recurrent Markov Processes. [PDF]
Li D, Li R.
europepmc +1 more source
ABSTRACT Ab initio path integral Monte Carlo (PIMC) simulations constitute the gold standard for the estimation of a broad range of equilibrium properties of a host of interacting quantum many‐body systems spanning a broad range of conditions from ultracold atoms to warm dense quantum plasmas.
Paul Hamann +2 more
wiley +1 more source
Subexponential lower bounds for <i>f</i>-ergodic Markov processes. [PDF]
Brešar M, Mijatović A.
europepmc +1 more source
Efficient maximum likelihood parameterization of continuous-time Markov processes. [PDF]
McGibbon RT, Pande VS.
europepmc +1 more source

