Bayesian Robust Multivariate Time Series Analysis in Nonlinear Regression Models with Vector Autoregressive and t-Distributed Errors

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OriginalspracheEnglisch
Titel des SammelwerksX Hotine-Marussi Symposium on Mathematical Geodesy
UntertitelProceedings of the Symposium, 2022
Herausgeber/-innenJeffrey T. Freymueller, Laura Sánchez
ErscheinungsortBerlin, Heidelberg
Seiten93-99
Seitenumfang7
PublikationsstatusVeröffentlicht - 2024

Publikationsreihe

NameInternational Association of Geodesy Symposia
Band155
ISSN (Print)0939-9585
ISSN (elektronisch)2197-9359

Abstract

Geodetic measurements rely on high-resolution sensors, but produce data sets with many observations which may contain outliers and correlated deviations. This paper proposes a powerful solution using Bayesian inference. The observed data is modeled as a multivariate time series with a stationary autoregressive (VAR) process and multivariate t-distribution for white noise. Bayes’ theorem integrates prior knowledge. Parameters, including functional, VAR coefficients, scaling, and degree of freedom of the t-distribution, are estimated with Markov Chain Monte Carlo using a Metropolis-within-Gibbs algorithm.

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Bayesian Robust Multivariate Time Series Analysis in Nonlinear Regression Models with Vector Autoregressive and t-Distributed Errors. / Dorndorf, Alexander; Kargoll, Boris; Paffenholz, Jens-André et al.
X Hotine-Marussi Symposium on Mathematical Geodesy: Proceedings of the Symposium, 2022. Hrsg. / Jeffrey T. Freymueller; Laura Sánchez. Berlin, Heidelberg, 2024. S. 93-99 (International Association of Geodesy Symposia; Band 155).

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandBeitrag in Buch/SammelwerkForschungPeer-Review

Dorndorf, A, Kargoll, B, Paffenholz, J-A & Alkhatib, H 2024, Bayesian Robust Multivariate Time Series Analysis in Nonlinear Regression Models with Vector Autoregressive and t-Distributed Errors. in JT Freymueller & L Sánchez (Hrsg.), X Hotine-Marussi Symposium on Mathematical Geodesy: Proceedings of the Symposium, 2022. International Association of Geodesy Symposia, Bd. 155, Berlin, Heidelberg, S. 93-99. https://doi.org/10.1007/1345_2023_210
Dorndorf, A., Kargoll, B., Paffenholz, J.-A., & Alkhatib, H. (2024). Bayesian Robust Multivariate Time Series Analysis in Nonlinear Regression Models with Vector Autoregressive and t-Distributed Errors. In J. T. Freymueller, & L. Sánchez (Hrsg.), X Hotine-Marussi Symposium on Mathematical Geodesy: Proceedings of the Symposium, 2022 (S. 93-99). (International Association of Geodesy Symposia; Band 155).. https://doi.org/10.1007/1345_2023_210
Dorndorf A, Kargoll B, Paffenholz JA, Alkhatib H. Bayesian Robust Multivariate Time Series Analysis in Nonlinear Regression Models with Vector Autoregressive and t-Distributed Errors. in Freymueller JT, Sánchez L, Hrsg., X Hotine-Marussi Symposium on Mathematical Geodesy: Proceedings of the Symposium, 2022. Berlin, Heidelberg. 2024. S. 93-99. (International Association of Geodesy Symposia). Epub 2023 Sep 6. doi: 10.1007/1345_2023_210
Dorndorf, Alexander ; Kargoll, Boris ; Paffenholz, Jens-André et al. / Bayesian Robust Multivariate Time Series Analysis in Nonlinear Regression Models with Vector Autoregressive and t-Distributed Errors. X Hotine-Marussi Symposium on Mathematical Geodesy: Proceedings of the Symposium, 2022. Hrsg. / Jeffrey T. Freymueller ; Laura Sánchez. Berlin, Heidelberg, 2024. S. 93-99 (International Association of Geodesy Symposia).
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