Difference between revisions of "CSEP Minutes 02-20-2019"

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(Created page with "CSEP Working Group Home Page<br><br> ''Participants'': D. Jackson, W. Savran, D. Rhoades, A. Michael, M. Werner, W. Marzocchi and P. Maechling * Use h...")
 
 
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[[CSEP_Working_Group|CSEP Working Group Home Page]]<br><br>
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[[CSEP_Working_Group|CSEP Working Group Home Page]]<br>
  
''Participants'': D. Jackson, W. Savran, D. Rhoades, A. Michael, M. Werner, W. Marzocchi and P. Maechling
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''Participants'': D. Jackson, W. Savran, D. Rhoades, A. Michael, M. Werner and W. Marzocchi
  
 
* Use histograms as opposed to ECDF using some type of cumulative statistic.  
 
* Use histograms as opposed to ECDF using some type of cumulative statistic.  

Latest revision as of 02:26, 21 February 2019

CSEP Working Group Home Page

Participants: D. Jackson, W. Savran, D. Rhoades, A. Michael, M. Werner and W. Marzocchi

  • Use histograms as opposed to ECDF using some type of cumulative statistic.
  • The K-S statistic provides biased values bc we are likely always going to be seeing largest differences at the greatest magnitudes, move to cumulative statistics.
  • Could also start the test above magnitudes of interest with a significance of earthquake hazard.
  • Imagine a hierarchy of tests that starts at a high-level and becomes more granular.
  • Look into the discrepancy in the ECDF.
  • Conditional magnitude test based on the observed number of events, this would involve some type of sampling based of the combined distribution.
  • Spatial distribution is very important, could be important more so than the number-distribution of the forecast; from USGS perspective.
  • What is interesting about UCERF3-ETAS:
    • Spatial distribution is most important and the differentiator between UCERF3-ETAS and regular ETAS.
    • Time-frame matters; most catalogs are computed for long times such that most catalogs are circular.
    • The value of the model might be seen from the long-term behavior of the model.
  • We could bin the models spatially and perform the N-test. We’d want to know how the models vary at the different between look-ahead times.
  • Need effective ways of communicating CSEP tests with the public. Tests should be accompanied with meaningful figures. See figures from the USGS wrt spatial forecasts.
  • Think about aggregate testing, for example, within Italy, people are interested in final outcomes. A powerful way is to use some sort of tool that David mentioned of plotting the time varying results.
  • Look at the weather forecasting community.