Estimation of the upper cutoff parameter for the tapered Pareto distribution
By Y. Kagan, Frederic Paik Schoenberg. Journal of Applied Probability, 2001
130 citations recorded by the source corpus.
Subfields: Finance, Geophysics, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/109f01000e04f808d735857232e52056c55b7c3a
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Finance
- Y. Kagan
- Frederic Paik Schoenberg
- Didier Sornette
- Andrew J. Patton
- Anders Johansen
- Valentyn Panchenko
- Daniel Berg
In Geophysics
- Alejandro Veen
- Frederic Paik Schoenberg
- Didier Sornette
- Y. Kagan
- R. Clements
- V. Pisarenko
- Agnes Helmstetter
- D. Jackson
In Statistics and Probability
- Y. Kagan
- Frederic Paik Schoenberg
- J. Woods
- Roger D. Peng
- R. Clements
- Carl Boettiger
- Hans Ekkehard Plesser
- Odd Erik Gundersen
Citations in the corpus
- On the distribution of wildfire sizes (2003, background): “In the field of seismology, similar considerations led to the use of the tapered Pareto distribution (Jackson and Kagan, 1999; Vere-Jones et al. 2000; Kagan and Schoenberg, 2001).”
- Evaluation of space–time point process models using super‐thinning (2011, background): “Following Kagan and Schoenberg (2001), the tapered Gutenberg–Richter density function is defined as f .s/D ˇ s C 1 M .m0/ s exp .m0/ s M .m0/6 s <1 where s is the scalar seismic moment (rather than magnitude) of a given earthquake, ˇ is a shape parameter, M is an upper cutoff parameter that…”
- Characterization of the Frequency of Extreme Earthquake Events by the Generalized Pareto Distribution (2000, background): “The strong statistical significance of our tests justifies the quest for a parametric representation of these deviations (Kagan and Schoenberg, 2000).”
- Seismic moment distribution revisited: I. Statistical results (2002, background): “For the TGR distribution Kagan & Schoenberg (2001) describe the results of simulating earthquake catalogues and evaluating the corner moment.”
- An extreme value approach for modeling Operational Risk losses depending on covariates (2016, unknown): “Our concentration on an example from the financial services industry also highlights the recent interest shown in more stringent capital buffers for banks (under the Basel guidelines) and insurance (referring to Solvency 2); for some background on these regularity frameworks, see for instance McNeil”