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Register a new userTesting Tail Weight of a Distribution Via Hazard Rate
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Added by
Kavya Ravichandran
Publication date
2020
fields
Informatics Engineering
and research's language is
English
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Understanding the shape of a distribution of data is of interest to people in a great variety of fields, as it may affect the types of algorithms used for that data. Given samples from a distribution, we seek to understand how many elements appear infrequently, that is, to characterize the tail of the distribution. We develop an algorithm based on a careful bucketing scheme that distinguishes heavy-tailed distributions from non-heavy-tailed ones via a definition based on the hazard rate under some natural smoothness and ordering assumptions. We verify our theoretical results empirically.
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