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Shift-Msplit Estimation in Deformation Analyses
AbstractThis paper presents an estimation method allowing direct and robust outlier assessment of parameter shifts in functional models of geodetic observations. The systems adopted in the discussion refer to functional models used in geodetic network deformation analysis. The proposed method is a robustness-oriented development of Shift-Msplit estimation. The problem of robustness is solved using an additional random variable with realizations that are outliers. The paper shows that the application of this variable also facilitates the selection of the appropriate number of competitive models in Msplit(q) estimation. Two numerical examples explain the manner of Shift-Msplit∗ estimation performance and indicate the basic properties of the determined estimates.
Shift-Msplit Estimation in Deformation Analyses
AbstractThis paper presents an estimation method allowing direct and robust outlier assessment of parameter shifts in functional models of geodetic observations. The systems adopted in the discussion refer to functional models used in geodetic network deformation analysis. The proposed method is a robustness-oriented development of Shift-Msplit estimation. The problem of robustness is solved using an additional random variable with realizations that are outliers. The paper shows that the application of this variable also facilitates the selection of the appropriate number of competitive models in Msplit(q) estimation. Two numerical examples explain the manner of Shift-Msplit∗ estimation performance and indicate the basic properties of the determined estimates.
Shift-Msplit Estimation in Deformation Analyses
Wiśniewski, Z (author) / Zienkiewicz, M. H
2016
Article (Journal)
English
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