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Abstract:
Ben-Ari and Schinazi (2016) introduced a stochastic model to study ‘virus-like evolving population with high mutation rate'. This model is a birth and death model with an individual at birth being either a mutant with a random fitness parameter in $[0,1]$ or having one of the existing fitness parameters with uniform probability; whereas a death event removes the entire population of the least fit site. We change this to incorporate the notion of ‘survival of the fittest‘, by requiring that a non-mutant individual, at birth, has a fitness according to a preferential attachment mechanism, i.e., it has a fitness $f$ with a probability proportional to the size of the population of fitness $f$. Also death just removes one individual at the least fit site. This preferential attachment rule leads to a power law behaviour in the asymptotics, unlike the exponential behaviour obtained by Ben-Ari and Schinazi (2016).
This is joint work with Hideki Tanemura (Keio University).
Biography:
Rahul Roy is a professor at the Indian Statistical Institute, New Delhi. He is a Fellow of the Indian Academy of Sciences.
His interests in probability and stochastic processes are primarily in the fields of percolation and random graphs.
Seminar by the NYU-ECNU Institute of Mathematical Sciences at NYU Shanghai