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An algorithm for testing heavy-tailed distributions

Author(s)
Ravichandran, Kavya.
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Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
Ronitt Rubinfeld.
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MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided. http://dspace.mit.edu/handle/1721.1/7582
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Abstract
Efficiently testing whether distributions have certain properties is a problem important in many different disciplines. We seek to understand how many elements appear infrequently, that is, characterize the tail of the distribution. In particular, we develop an algorithm that determines whether the weight of the tail of a distribution is heavy (such as a Lomax) or exponential. Our algorithm makes use of an equal weight bucketing scheme that divides the support of the distribution according to how much probability mass lies between two points, allowing us to characterize parts of the distribution we may not see many samples from. We analyze the sample complexity of our test statistic.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, May, 2020
 
Cataloged from the official PDF of thesis.
 
Includes bibliographical references (pages 41-42).
 
Date issued
2020
URI
https://hdl.handle.net/1721.1/127508
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.

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