Topics in stochastic growth models

Thumbnail Image
Date
2013-01-01
Authors
Ghosh, Subhomoy
Major Professor
Advisor
Arka P. Ghosh
Alexander Roitershtein
Committee Member
Journal Title
Journal ISSN
Volume Title
Publisher
Altmetrics
Authors
Research Projects
Organizational Units
Organizational Unit
Statistics
As leaders in statistical research, collaboration, and education, the Department of Statistics at Iowa State University offers students an education like no other. We are committed to our mission of developing and applying statistical methods, and proud of our award-winning students and faculty.
Journal Issue
Is Version Of
Versions
Series
Department
Abstract

Stochastic growth models are very common in real life owing to their ability to capture the underlying mechanisms. This thesis considers three of such models. Each model can be seen as describing the evolution in time of a complex population of interacting ``particles": competing types of individuals in the first model, nodes in a dynamic network in the second, and species in an ecosystem in the third. A common feature of these models is that the population size grows in time and is represented by a transient (generalized) birth and death Markov process. This dissertation studies asymptotic structure of the ``particles landscape" which is represented in these three models by, respectively, type structure of the population, graph of interconnections, and the empirical distribution of species fitness.

Comments
Description
Keywords
Citation
Source
Subject Categories
Copyright
Tue Jan 01 00:00:00 UTC 2013