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Here, we propose an adaptive random walk (ARW), which, differently from the maximum entropy random walk, maximizes dispersion by updating its transition rule on the local information collected while exploring the network. The ARW is obtained via a large-deviation representation of the MERW as a finite-time rare event of an unbiased random walk and study its dynamics on synthetic and real-world networks.
This project is an implementation of the Adaptive Power Method (APM). It simulates a random walk on an Erdős-Rényi random graph to compute the scaled culumant generating function (SCGF) and rate function of the mean degree a time additive observable.
Code developed for a research project at the University of Cambridge, supervised by Robert Jack.
We derive asymptotic behavior of the probability of high-level excursion for the maximal increment of a Gaussian random walk.
We derive asymptotic behavior of the probability of high-level excursion for the maximal increment of the Wiener process.
Most of my writings — notes, talks, travelogues, thoughts, and the rest
Wiki of a research project at the University of Cambridge, supervised by Robert Jack, and at the Université de Paris, supervised by Frédéric van Wijland.
LD-SPATT (spatt, statistics for patterns) gsl 2.1 on Win64. VC2015. ported to win64. Large Deviation on coin tosses in s/h. And on Markov Sequences in C++ code.. Also excel s/h
Source code of paper "Rare Events of Host Switching for Diseases using a SIR Model with Mutations"