An algorithm for testing heavy-tailed distributions
Name
1193028613-MIT.pdf
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8.84 MB
Format
Adobe PDF
Checksum (MD5)
a81ebda6818e29efcf06feda9b0b691d
Author(s)
Ravichandran, Kavya.
Advisor(s)
Ronitt Rubinfeld.
Date Issued
2020
Publisher
Massachusetts Institute of Technology
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).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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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.
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