Modeling and approximating non-stationarities in stochastic systems
Abstract/Contents
- Abstract
- This dissertation consists of two parts, with a central focus on modeling and approximating non-stationarities in stochastic systems. The first part revolves around the statistical and stochastic modeling of the non-stationary arrivals that serve as inputs to such systems. The second part revolves around approximating performances for stochastic systems with non-stationary dynamics or non-stationary inputs.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2018; ©2018 |
| Publication date | 2018; 2018 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Zheng, Zeyu |
|---|---|
| Degree supervisor | Glynn, Peter W |
| Thesis advisor | Glynn, Peter W |
| Thesis advisor | Bambos, Nicholas |
| Thesis advisor | Blanchet, Jose H |
| Degree committee member | Bambos, Nicholas |
| Degree committee member | Blanchet, Jose H |
| Associated with | Stanford University, Department of Management Science and Engineering. |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Zeyu Zheng. |
|---|---|
| Note | Submitted to the Department of Management Science and Engineering. |
| Thesis | Thesis Ph.D. Stanford University 2018. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2018 by Zeyu Zheng
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
Also listed in
Loading usage metrics...