2 citations · 2 across the 5 of their papers we have counts for
5 papers
Assessing Risk Heterogeneity through Heavy-Tailed Frequency and Severity Mixtures
Michael R. Powers, Jiaxin Xu
The analysis of risk typically involves dividing a random damage-generation process into separate frequency (event-count) and severity (damage-magnitude) components. In the present…
A Criterion for Extending Continuous-Mixture Identifiability Results
Michael R. Powers, Jiaxin Xu
Mixture distributions provide a versatile and widely used framework for modeling random phenomena, and are particularly well-suited to the analysis of geoscientific processes and t…
A Versatility Measure for Parametric Risk Models
Michael R. Powers, Jiaxin Xu
Parametric statistical methods play a central role in analyzing risk through its underlying frequency and severity components. Given the wide availability of numerical algorithms a…
Heavy-Tailed Loss Frequencies from Mixtures of Negative Binomial and Poisson Counts
Jiansheng Dai, Ziheng Huang, Michael R. Powers +1
Heavy-tailed random variables have been used in insurance research to model both loss frequencies and loss severities, with substantially more emphasis on the latter. In the presen…
Characterizing the Zeta Distribution via Continuous Mixtures
Jiansheng Dai, Ziheng Huang, Michael R. Powers +1
We offer two novel characterizations of the Zeta distribution: first, as tractable continuous mixtures of Negative Binomial distributions (with fixed shape parameter, r > 0), and s…