ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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- Genre: Masters Thesis
- Genre: Diaries
to stimuli presented to subjects in a scanner. It is important to conduct statistical
inference on such time series fMRI data obtained. It is also important to select optimal designs for practical experiments. Design selection under autoregressive models
have not been thoroughly discussed before. This paper derives general information
matrices for orthogonal designs under autoregressive model with an arbitrary number
of correlation coefficients. We further provide the minimum trace of orthogonal circulant designs under AR(1) model, which is used as a criterion to compare practical
designs such as M-sequence designs and circulant (almost) orthogonal array designs.
We also explore optimal designs under AR(2) model. In practice, types of stimuli can
be more than one, but in this paper we only consider the simplest situation with only
one type of stimuli.