Monte Carlo methods for structured data
Abstract/Contents
- Abstract
- Sequential importance sampling is well known to have difficulties in high-dimensional settings. I present a technique called conditional sampling-importance resampling, an extension of sampling importance resampling to conditional distributions that improves performance, particularly when independence structure is present. The primary application is to multi-object tracking for a colony of harvester ants in a laboratory setting. Previous approaches tend to make simplifying parametric assumptions on the model in order to make computations more tractable, while the approach presented finds approximate solutions to more complicated and realistic models. To analyze structural properties of networks, I expand adaptive importance sampling techniques to the analysis of network growth models such as preferential attachment, using the Plackett-Luce family of distributions on permutations, and I present an application of sequential Monte Carlo to a special form of network growth model called vertex censored stochastic Kronecker product graphs.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2012 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Guetz, Adam Nathan |
|---|---|
| Associated with | Stanford University, Institute for Computational and Mathematical Engineering. |
| Primary advisor | Holmes, Susan, 1954- |
| Primary advisor | Saberi, Amin |
| Thesis advisor | Holmes, Susan, 1954- |
| Thesis advisor | Saberi, Amin |
| Thesis advisor | Glynn, Peter W |
| Advisor | Glynn, Peter W |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Adam Guetz. |
|---|---|
| Note | Submitted to the Institute for Computational and Mathematical Engineering. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2012. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2012 by Adam Nathan Guetz
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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