Realistic Simulations of Geodetic Network Data: The Fakenet Package

Online Material: Program manual, source code, and associated files. 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 a different realization of the noise added to a different signal known only to the creator of the dataset. The Fakenet package was written to provide software for creating these datasets. In developing Fakenet, the goals were to be able to: This paper describes the procedures used in this package, as well as outlining its structure. A user’s manual is available in ![Graphic][1] the electronic supplement to this paper. It describes the details of operation, installation procedures, and the file formats. The supplement also includes the software itself, … [1]: /embed/inline-graphic-1.gif

[1]  S. T. Buckland,et al.  An Introduction to the Bootstrap. , 1994 .

[2]  Yehuda Bock,et al.  Southern California permanent GPS geodetic array: Spatial filtering of daily positions for estimating coseismic and postseismic displacements induced by the 1992 Landers earthquake , 1997 .

[3]  Y. Bock,et al.  Space geodetic observation of expansion of the San Gabriel Valley, California, aquifer system, during heavy rainfall in winter 2004–2005 , 2007 .

[4]  Yehuda Bock,et al.  Error analysis of continuous GPS position time series , 2004 .

[5]  S. K. Park,et al.  Random number generators: good ones are hard to find , 1988, CACM.

[6]  Takuji Nishimura,et al.  Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator , 1998, TOMC.

[7]  Wayne Luk,et al.  Gaussian random number generators , 2007, CSUR.

[8]  Jan Beran,et al.  On a class of M-estimators for Gaussian long-memory models , 1994 .

[9]  T. Dixon,et al.  Noise in GPS coordinate time series , 1999 .

[10]  Jonathan M. Lees.  Open and Free: Software and Scientific Reproducibility , 2012 .

[11]  Y. Okada.  Surface deformation due to shear and tensile faults in a half-space , 1985 .

[12]  Pierre L'Ecuyer,et al.  TestU01: A C library for empirical testing of random number generators , 2006, TOMS.

[13]  John Langbein,et al.  Noise in GPS displacement measurements from Southern California and Southern Nevada , 2008 .

[14]  Simon D. P. Williams,et al.  Offsets in Global Positioning System time series , 2003 .

[15]  Simon D. P. Williams,et al.  CATS: GPS coordinate time series analysis software , 2008 .

[16]  John Langbein,et al.  Correlated errors in geodetic time series: Implications for time‐dependent deformation , 1997 .

[17]  M. Tamisiea,et al.  On seasonal signals in geodetic time series , 2012 .

[18]  Jill P Mesirov,et al.  Accessible Reproducible Research , 2010, Science.

[19]  Simon D. P. Williams,et al.  Fast error analysis of continuous GPS observations , 2008 .

[20]  R. Bennett.  Instantaneous deformation from continuous GPS: Contributions from quasi-periodic loads , 2008 .