Evaluation of Interpolants in Their Ability to Fit Seismometric Time Series

Kanadpriya Basu, Maria C. Mariani, Laura Serpa and Ritwik Sinha
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Kanadpriya Basu: Department of Mathematical Sciences, University of Texas at El Paso, Bell Hall 220, El Paso, TX 79968-0514, USA
Maria C. Mariani: Department of Mathematical Sciences, University of Texas at El Paso, Bell Hall 124, El Paso, TX 79968-0514, USA
Laura Serpa: Department of Geological Sciences, University of Texas at El Paso, El Paso, TX 79968-0514, USA
Ritwik Sinha: Adobe Research and Development Pvt. Limited, Bangalore-560029, India

Mathematics, 2015, vol. 3, issue 3, 1-24

Abstract: This article is devoted to the study of the ASARCO demolition seismic data. Two different classes of modeling techniques are explored: First, mathematical interpolation methods and second statistical smoothing approaches for curve fitting. We estimate the characteristic parameters of the propagation medium for seismic waves with multiple mathematical and statistical techniques, and provide the relative advantages of each approach to address fitting of such data. We conclude that mathematical interpolation techniques and statistical curve fitting techniques complement each other and can add value to the study of one dimensional time series seismographic data: they can be use to add more data to the system in case the data set is not large enough to perform standard statistical tests.

Keywords: spline smoothing; interpolation methods; loess methods; statistical smoothing; geophysics; seismic data (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2015
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