Statistical analysis of astro-geodetic data through principal component analysis, linear modelling and bootstrap based inference
The paper demonstrates the application of statistical based methodology for the analysis of the vertical deviation angle. The studied data set contains astro-geodetic observations. The Principal Component Analysis and the Multiple Linear Regression models are embedded within a bootstrap procedure, i...
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Main Authors | , , , , |
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Format | Journal Article |
Language | English |
Published |
20.09.2018
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Subjects | |
Online Access | Get full text |
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Summary: | The paper demonstrates the application of statistical based methodology for
the analysis of the vertical deviation angle. The studied data set contains
astro-geodetic observations. The Principal Component Analysis and the Multiple
Linear Regression models are embedded within a bootstrap procedure, in order to
overcome the difficulties related to data correlation, while taking advantage
of all the information provided. The methodology is applied on real data. The
obtained results indicate that the pressure, the temperature and the humidity
are variables that may influence the measure of the vertical deviation. |
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DOI: | 10.48550/arxiv.1809.07879 |