Large deviation principles for random measures Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/h415pd111

Descriptions

Attribute NameValues
Creator
Abstract or Summary
  • Large deviation theory has experienced much development and interest in the last two decades. A large deviation principle is the exponential decay of the probability of increasingly rare events and the computation of a rate or entropy function which measures the rate of decay. Within the probability literature there has been much use made of these rates in diverse applications. These large deviation principles have been discovered for independent and identically distributed random variables, as well as random vectors and these have been extended to some cases of weak dependence. In this thesis we prove large deviation principles for finite dimensional distributions of scaling limits of random measures. Functional approaches to large deviation theory using test functions as dual objects to random measures are also developed. These results are applied to some important classes of models, in particular Poisson point processes, Poisson center cluster processes and doubly stochastic point processes.
Resource Type
Date Available
Date Issued
Degree Level
Degree Name
Degree Field
Degree Grantor
Commencement Year
Advisor
Committee Member
Academic Affiliation
Non-Academic Affiliation
Subject
Rights Statement
Language
Digitization Specifications
  • Master files scanned at 600 ppi (256 Grayscale) using Capture Perfect 3.0.82 on a Canon DR-9080C in TIF format. PDF derivative scanned at 300 ppi (256 B&W), using Capture Perfect 3.0.82, on a Canon DR-9080C. CVista PdfCompressor 4.0 was used for pdf compression and textual OCR.
Replaces
Additional Information
  • description.provenance : Approved for entry into archive by Patricia Black(patricia.black@oregonstate.edu) on 2010-06-11T15:46:59Z (GMT) No. of bitstreams: 1 HwangDae-Sik.pdf: 429245 bytes, checksum: 840f6f2bbe71eb274276b7feab565314 (MD5)
  • description.provenance : Submitted by Joe Nguyen (jnscanner@gmail.com) on 2010-06-01T22:27:12Z No. of bitstreams: 1 HwangDae-Sik.pdf: 429245 bytes, checksum: 840f6f2bbe71eb274276b7feab565314 (MD5)
  • description.provenance : Made available in DSpace on 2010-06-11T15:50:22Z (GMT). No. of bitstreams: 1 HwangDae-Sik.pdf: 429245 bytes, checksum: 840f6f2bbe71eb274276b7feab565314 (MD5)
  • description.provenance : Approved for entry into archive by Patricia Black(patricia.black@oregonstate.edu) on 2010-06-11T15:50:22Z (GMT) No. of bitstreams: 1 HwangDae-Sik.pdf: 429245 bytes, checksum: 840f6f2bbe71eb274276b7feab565314 (MD5)

Relationships

In Administrative Set:
Last modified: 08/08/2017

Downloadable Content

Download PDF
Citations:

EndNote | Zotero | Mendeley

Items