1 / 3

Data Uncertainties :

Data Uncertainties :. Reduced chi-square misfit of data. Most input data are weighted by 1/variance. Angular data. Some slip rates are given by min/max range. Parameter uncertainties:. ‘Formal’ uncertainties estimated by TDEFNODE are linearized.

cecily
Download Presentation

Data Uncertainties :

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Data Uncertainties: Reduced chi-square misfit of data Most input data are weighted by 1/variance Angular data Some slip rates are given by min/max range

  2. Parameter uncertainties: • ‘Formal’ uncertainties estimated by TDEFNODE are linearized. • Parameter covariance matrix is (MTWM)-1 where M is matrix of partial derivatives and W is weight matrix. • M = | datum/parameter | • Other strategies: • Runs with parameter fixed at multiple values • Bootstrapping • Monte Carlo (add noise and invert many times) • Hypothesis testing

  3. Fixing slip rate on AL fault and running inversion with remaining parameters free

More Related