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MIDAS robust trend estimator for accurate GPS station velocities without step detection / Geoffrey Blewitt in Journal of geophysical research : Solid Earth, vol 121 n° 3 (March 2016)    

Public [article]  inJournal of geophysical research : Solid Earth > vol 121 n° 3 (March 2016) . - pp 2054 - 2068 Titre : MIDAS robust trend estimator for accurate GPS station velocities without step detection Type de document : Article/Communication Auteurs : Geoffrey Blewitt, Auteur ; Corné Kremer, Auteur ; William C. Hammond, Auteur ; Julien Gazeaux , Auteur Année de publication : 2016 Article en page(s) : pp 2054 - 2068 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] Amérique du nord [Termes IGN] coordonnées GPS [Termes IGN] estimateur [Termes IGN] méthode robuste [Termes IGN] série temporelle [Termes IGN] station GPS [Termes IGN] valeur aberrante [Termes IGN] vitesse Résumé : (auteur) Automatic estimation of velocities from GPS coordinate time series is becoming required to cope with the exponentially increasing flood of available data, but problems detectable to the human eye are often overlooked. This motivates us to find an automatic and accurate estimator of trend that is resistant to common problems such as step discontinuities, outliers, seasonality, skewness, and heteroscedasticity. Developed here, Median Interannual Difference Adjusted for Skewness (MIDAS) is a variant of the Theil‐Sen median trend estimator, for which the ordinary version is the median of slopes vij = (xj–xi)/(tj–ti) computed between all data pairs i > j. For normally distributed data, Theil‐Sen and least squares trend estimates are statistically identical, but unlike least squares, Theil‐Sen is resistant to undetected data problems. To mitigate both seasonality and step discontinuities, MIDAS selects data pairs separated by 1 year. This condition is relaxed for time series with gaps so that all data are used. Slopes from data pairs spanning a step function produce one‐sided outliers that can bias the median. To reduce bias, MIDAS removes outliers and recomputes the median. MIDAS also computes a robust and realistic estimate of trend uncertainty. Statistical tests using GPS data in the rigid North American plate interior show ±0.23 mm/yr root‐mean‐square (RMS) accuracy in horizontal velocity. In blind tests using synthetic data, MIDAS velocities have an RMS accuracy of ±0.33 mm/yr horizontal, ±1.1 mm/yr up, with a 5th percentile range smaller than all 20 automatic estimators tested. Considering its general nature, MIDAS has the potential for broader application in the geosciences. Numéro de notice : A2016--176 Affiliation des auteurs : LASTIG LAREG+Ext (2012-mi2018) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1002/2015JB012552 Date de publication en ligne : 12/02/2016 En ligne : https://doi.org/10.1002/2015JB012552 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91799 [article]

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