Testing infection graphs / Justin Turner Khim.

Format:

Book

Manuscript

Thesis/Dissertation

Author/Creator:

Khim, Justin Turner, author.

Contributor:

Ma, Zongming, degree supervisor.

Small, Dylan, degree committee member.

Rakhlin, Alexander, degree committee member.

Loh, Po-Ling, degree committee member.

University of Pennsylvania. Department of Statistics, degree granting institution.

Language:

English

Subjects (All):

Penn dissertations--Statistics.

Statistics--Penn dissertations.

Local Subjects:

Penn dissertations--Statistics.

Statistics--Penn dissertations.

Physical Description:

ix, 106 leaves : illustrations ; 29 cm

Production:

[Philadelphia, Pennsylvania] : University of Pennsylvania, 2019.

Summary:

We study the following problem: given two graphs G0 and G1 defined on a common set of n vertices and a single observation of the statuses of these vertices, i.e. either infected, uninfected, or censored, did the infection spread on G0 or G1? Modern instances of such "infections" include diseases such as HIV, behaviors such as smoking, or information such as online news articles. For particular stochastic spreading mechanisms, we give algorithms for this testing problem based on hypothesis discretization and permutation-invariance. Additionally, these methods also lead to confidence sets for parameters that also govern the spread of infection and for the graphs on which the infection spread.

Notes:

Ph. D. University of Pennsylvania 2019.

Department: Statistics.

Supervisor: Zongming Ma.

Includes bibliographical references.

Other Format:

Online version: Khim, Justin Turner. Testing infection graphs.

OCLC:

1127393008