What's new
Warez.Ge

This is a sample guest message. Register a free account today to become a member! Once signed in, you'll be able to participate on this site by adding your own topics and posts, as well as connect with other members through your own private inbox!

Asymptotic Properties of Permanental Sequences

voska89

Moderator
Staff member
1b0c875bf32329c221e6bd74c435614b.jpeg

Asymptotic Properties of Permanental Sequences: Related to Birth and Death Processes and Autoregressive Gaussian Sequences by Michael B. Marcus, Jay Rosen
English | EPUB | 2021 | 128 Pages | ISBN : 3030694844 | 8.8 MB​

This SpringerBriefs 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.
This SpringerBriefs 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.


Recommend Download Link Hight Speed | Please Say Thanks Keep Topic Live
Links are Interchangeable - No Password - Single Extraction
 

Users who are viewing this thread

Back
Top