Yi, Bowen B
(2018)
Inference based on boundary crossing of diffusions.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
Abstract
Nowadays, the boundary crossing problem of diffusion processes is of interest to both mathematicians and statisticians. In this thesis, we review the literature on the first passage time problem for both one-dimensional and two-dimensional diffusion processes. Then we investigate the statistical inference problem about unknown parameters of the Cox-Ingersoll-Ross model based on discretely observed first passage times. We are able to determine the identifiable parameter set, discuss the tail property of the density function in a neighborhood of the true parameter, and propose a conditional version of maximum likelihood estimation. We also list future work, including extensions of this problem to a general one-dimensional time homogeneous diffusion process, and to some special two-dimensional diffusion processes.
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Details
Item Type: |
University of Pittsburgh ETD
|
Status: |
Unpublished |
Creators/Authors: |
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ETD Committee: |
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Date: |
26 September 2018 |
Date Type: |
Publication |
Defense Date: |
23 July 2018 |
Approval Date: |
26 September 2018 |
Submission Date: |
1 August 2018 |
Access Restriction: |
1 year -- Restrict access to University of Pittsburgh for a period of 1 year. |
Number of Pages: |
89 |
Institution: |
University of Pittsburgh |
Schools and Programs: |
Dietrich School of Arts and Sciences > Statistics |
Degree: |
PhD - Doctor of Philosophy |
Thesis Type: |
Doctoral Dissertation |
Refereed: |
Yes |
Uncontrolled Keywords: |
First passage time, Cox-Ingersoll-Ross model, Maximum likelihood estimation |
Date Deposited: |
26 Sep 2018 23:21 |
Last Modified: |
19 Jul 2024 19:16 |
URI: |
http://d-scholarship.pitt.edu/id/eprint/35083 |
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