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Yuguang Ipsen
Researcher at Australian National University
Publications - 16
Citations - 77
Yuguang Ipsen is an academic researcher from Australian National University. The author has contributed to research in topics: Subordinator & Negative binomial distribution. The author has an hindex of 5, co-authored 16 publications receiving 55 citations.
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Phishing and Cybercrime Risks in a University Student Community
TL;DR: In an exploratory quasi-experimental observational study, 138 participants recruited during a university orientation week were exposed to social engineering directives in the form of fake email or phishing attacks over several months in 2017 as discussed by the authors.
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Limiting Distributions of Generalised Poisson–Dirichlet Distributions Based on Negative Binomial Processes
TL;DR: In this paper, it was shown that other distributions on the simplex, such as the Poisson-Dirichlet distribution, occur as limiting cases of the two-parameter distribution for random vectors on the infinite simplex.
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Negative Binomial Construction of Random Discrete Distributions on the Infinite Simplex
Yuguang Ipsen,Ross Maller +1 more
TL;DR: In this paper, a negative binomial point process with parameter $r>0$ and L\'evy density was introduced, which is a new class of distributions on the infinite simplex.
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Convergence to stable limits for ratios of trimmed Levy processes and their jumps
TL;DR: In this paper, the authors derived characteristic function identities for conditional distributions of an r-trimmed Levy process given its r largest jumps up to a designated time t. Assuming the underlying Levy process is in the domain of attraction of a stable process as t goes to 0, these identities are applied to show joint convergence of the trimmed process divided by its large jumps to corresponding quantities constructed from a stable limiting process.
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Ratios of Ordered Points of Point Processes with Regularly Varying Intensity Measures
TL;DR: In this paper, the authors study limiting properties of ratios of ordered points of point processes whose intensity measures have regularly varying tails, giving a systematic treatment which points the way to "large-trimming" properties of extremal processes and a variety of applications.