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Least Squares Contribution to Geodetic Time Series Analysis,nalysis. The first part of the chapter is devoted to the functional model identification in which the presence and identification of outlying observations, offsets, and possible periodic signals in the series will be discussed. The second part deals with the parameter estimation in the stochastic moCOMA 发表于 2025-3-27 08:53:06
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2364-9119 gravity (ice sheet loss) and earthquakes respectively. It also provides a necessary overview of geodetic software and where to obtain them..978-3-030-21720-4978-3-030-21718-1Series ISSN 2364-9119 Series E-ISSN 2364-9127搜集 发表于 2025-3-27 23:55:56
,Schwierigkeiten des Heißluftbetriebes,are much less computationally intensive than comprehensive methods, such as maximum likelihood estimators. Our approaches are compared to other commonly used programs, such as Hector, to understand the speed and impact of outliers on the algorithms, and to provide advice and suggestions on the usesAnguish 发表于 2025-3-28 03:27:11
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Siegfried Gräff,Leopold Küpferleace models are defined and solved through the use of a Kalman Filter (KF). Special attention is paid towards carefully estimating the noise parameters, which is an essential step in the KF. It is demonstrated how the time-correlated observational noise can be classified and handled within the state-