Importance of probability levels for robustness analysis of geodetic networks

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dc.contributor.authorYetkin, M.
dc.contributor.authorBerber, M.
dc.contributor.authorInal, C.
dc.date.accessioned2020-03-26T18:51:03Z
dc.date.available2020-03-26T18:51:03Z
dc.date.issued2014
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractRobustness Analysis is a natural merger of reliability and strain and defined as the ability to resist deformations caused by the maximum undetectable errors. Internal reliability criterion describes maximum undetectable errors in observations, which would not be detected by Baarda's statistical testing method (data snooping) based on the chosen Type I and II error probabilities. The non-centrality parameter is a function of probability levels and it plays an important role in Robustness Analysis. In this paper, it is aimed to show the impact of non-centrality parameter on the displacements and the relationship between the selected confidence level for confidence regions and threshold values in a geodetic network. For a geodetic network example, a GPS network is chosen and computations of displacements and threshold values (derived from confidence regions) have been carried out for both in-context and out-of context approaches. According to our results, the non-centrality parameter controls the magnitudes of displacements without affecting their relative behaviours. Statistically, lower probability levels are desired. However, if error probabilities are decreased, the non-centrality parameter increases. Since, the non-centrality parameter scales the displacements, a balance between both types of decision error is needed to obtain displacement values that are smaller than threshold values in order to reach a totally robust network at the required level of probability.en_US
dc.description.sponsorshipScientific and Technological Research Council of Turkey at Florida Atlantic UniversityTurkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK)en_US
dc.description.sponsorshipThe first author wishes to acknowledge the support by The Scientific and Technological Research Council of Turkey for his research at Florida Atlantic University. The authors thank reviewers for their very helpful and constructive comments.en_US
dc.identifier.doi10.1179/1752270613Y.0000000065en_US
dc.identifier.endpage141en_US
dc.identifier.issn0039-6265en_US
dc.identifier.issn1752-2706en_US
dc.identifier.issue335en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage132en_US
dc.identifier.urihttps://dx.doi.org/10.1179/1752270613Y.0000000065
dc.identifier.urihttps://hdl.handle.net/20.500.12395/30916
dc.identifier.volume46en_US
dc.identifier.wosWOS:000337133800007en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherTAYLOR & FRANCIS LTDen_US
dc.relation.ispartofSURVEY REVIEWen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectRobustness analysisen_US
dc.subjectStatistical testingen_US
dc.subjectIn-context approachen_US
dc.subjectOut-of-context approachen_US
dc.subjectRelative displacementen_US
dc.subjectThreshold valueen_US
dc.titleImportance of probability levels for robustness analysis of geodetic networksen_US
dc.typeArticleen_US

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