Risking to underestimate the integrity risk

As parameter estimation and statistical testing are often intimately linked in the processing of observational data, the uncertainties involved in both estimation and testing need to be properly propagated into the final results produced. This necessitates the use of conditional distributions when e...

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Main Authors: Zaminpardaz, S., Teunissen, Peter, Tiberius, C.
Format: Journal Article
Published: Springer 2019
Online Access:http://hdl.handle.net/20.500.11937/74002
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author Zaminpardaz, S.
Teunissen, Peter
Tiberius, C.
author_facet Zaminpardaz, S.
Teunissen, Peter
Tiberius, C.
author_sort Zaminpardaz, S.
building Curtin Institutional Repository
collection Online Access
description As parameter estimation and statistical testing are often intimately linked in the processing of observational data, the uncertainties involved in both estimation and testing need to be properly propagated into the final results produced. This necessitates the use of conditional distributions when evaluating the quality of the resulting estimator. As the conditioning should be on the identified hypothesis as well as on the corresponding testing outcome, omission of the latter will result in an incorrect description of the estimator’s distribution. In this contribution, we analyse the impact this omission or approximation has on the considered distribution of the estimator and its integrity risk. For a relatively simple observational model it is mathematically proven that the rigorous integrity risk exceeds the approximation for the contributions under the null hypothesis, which typically has a much larger probability of occurrence than an alternative. Actual GNSS-based positioning examples confirm this finding. Overall we observe a tendency of the approximate integrity risk being smaller than the rigorous one. The approximate approach may, therefore, provide a too optimistic description of the integrity risk and thereby not sufficiently safeguard against possibly hazardous situations. We, therefore, strongly recommend the use of the rigorous approach to evaluate the integrity risk, as underestimating the integrity risk in practice, and also the risk to do so, cannot be acceptable particularly in critical and safety-of-life applications.
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spelling curtin-20.500.11937-740022019-05-03T00:06:54Z Risking to underestimate the integrity risk Zaminpardaz, S. Teunissen, Peter Tiberius, C. As parameter estimation and statistical testing are often intimately linked in the processing of observational data, the uncertainties involved in both estimation and testing need to be properly propagated into the final results produced. This necessitates the use of conditional distributions when evaluating the quality of the resulting estimator. As the conditioning should be on the identified hypothesis as well as on the corresponding testing outcome, omission of the latter will result in an incorrect description of the estimator’s distribution. In this contribution, we analyse the impact this omission or approximation has on the considered distribution of the estimator and its integrity risk. For a relatively simple observational model it is mathematically proven that the rigorous integrity risk exceeds the approximation for the contributions under the null hypothesis, which typically has a much larger probability of occurrence than an alternative. Actual GNSS-based positioning examples confirm this finding. Overall we observe a tendency of the approximate integrity risk being smaller than the rigorous one. The approximate approach may, therefore, provide a too optimistic description of the integrity risk and thereby not sufficiently safeguard against possibly hazardous situations. We, therefore, strongly recommend the use of the rigorous approach to evaluate the integrity risk, as underestimating the integrity risk in practice, and also the risk to do so, cannot be acceptable particularly in critical and safety-of-life applications. 2019 Journal Article http://hdl.handle.net/20.500.11937/74002 10.1007/s10291-018-0812-0 http://creativecommons.org/licenses/by/4.0/ Springer fulltext
spellingShingle Zaminpardaz, S.
Teunissen, Peter
Tiberius, C.
Risking to underestimate the integrity risk
title Risking to underestimate the integrity risk
title_full Risking to underestimate the integrity risk
title_fullStr Risking to underestimate the integrity risk
title_full_unstemmed Risking to underestimate the integrity risk
title_short Risking to underestimate the integrity risk
title_sort risking to underestimate the integrity risk
url http://hdl.handle.net/20.500.11937/74002