Realistic Simulations of Geodetic Network Data: The Fakenet Package
Duncan Carr Agnew · Seismological Research Letters · 2013
Research Article| May 01, 2013 Realistic Simulations of Geodetic Network Data: The Fakenet Package Duncan Carr Agnew Duncan Carr Agnew Institute of Geophysics and Planetary Physics, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California 92093‐0225 [email protected] Search for other works by this author on: GSW Google Scholar Author and Article Information Duncan Carr Agnew Institute of Geophysics and Planetary Physics, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California 92093‐0225 [email protected] Publisher: Seismological Society of America First Online: 09 Mar 2017 Online ISSN: 1938-2057 Print ISSN: 0895-0695 © 2013 by the Seismological Society of America Seismological Research Letters (2013) 84 (3): 426–432. https://doi.org/10.1785/0220120185 Article history First Online: 09 Mar 2017 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn Email Permissions Search Site Citation Duncan Carr Agnew; Realistic Simulations of Geodetic Network Data: The Fakenet Package. Seismological Research Letters 2013;; 84 (3): 426–432. doi: https://doi.org/10.1785/0220120185 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietySeismological Research Letters Search Advanced Search The Southern California Earthquake Center (SCEC) Transient Detection intercomparison required that all participants apply their methods to the same datasets, each dataset containing some tectonic signal (or none), plus realistic noise. One way to produce these would be to add tectonic signals to actual data from the California continuous GPS network (CCGPSN), but there are two problems with this: using the same background series for all datasets makes it easy to isolate signals by differencing, and we would not know if there was a transient already present in the data. Instead, fully synthetic datasets were used, each of which had... You do not have access to this content, please speak to your institutional administrator if you feel you should have access.