This Springer Briefs employs a novel approach to obtain the precise asymptotic behavior at infinity of a large class of permanental sequences related to birth and death processes and autoregressive Gaussian sequences using techniques from the theory of Gaussian processes and Markov chains.
The authors study alpha-permanental processes that are positive infinitely divisible processes determined by the potential density of a transient Markov process. When the Markov process is symmetric, a 1/2-permanental process is the square of a Gaussian process. Permanental processes are related by the Dynkin isomorphism theorem to the total accumulated local time of the Markov process when the potential density is symmetric, and by a generalization of the Dynkin theorem by Eisenbaum and Kaspi without requiring symmetry. Permanental processes are also related to chi square processes and loop soups.
The book appeals to researchers and advanced graduate students interested in stochastic processes, infinitely divisible processes and Markov chains.
İçerik tablosu
1.Introduction, General Results and Applications.- 2.Birth and death processes.- 3.Birth and death processes with emigration.- 4.Birth and death processes with emigration related to first order Gaussian autoregressive sequences.- 5.Markov chains with potentials that are the covariances of higher order Gaussian autoregressive sequences.- 6.Relating permanental sequences to Gaussian sequences.- 7. Permanental sequences with kernels that have uniformly bounded row sums.- 8.Uniform Markov chains.- References.- Index.
Yazar hakkında
Professor Marcus is Professor Emeritus at The City College, CUNY and the CUNY Graduate Center and Professor Rosen is Distinguished Professor at The College of Staten Island, CUNY and the CUNY Graduate Center. Together they have published more than two hundred papers of which thirty six were written jointly and five books three of which were written jointly. Together they have delivered more than three hundred invited talks. Their research is on sample path properties of stochastic processes, specializing in Gaussian processes, random Fourier series, Gaussian chaos, Levy processes, Markov processes, local times, intersection local times, loop soups and permanental processes.
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