Lüttschwager, Nils O. B.

[["dc.bibliographiccitation.artnumber","3526"],["dc.bibliographiccitation.issue","64"],["dc.bibliographiccitation.journal","The Journal of Open Source Software"],["dc.bibliographiccitation.volume","6"],["dc.contributor.author","Lüttschwager, Nils O. B."],["dc.date.accessioned","2022-04-28T06:59:43Z"],["dc.date.available","2022-04-28T06:59:43Z"],["dc.date.issued","2021-08-31"],["dc.description.abstract","The evaluation of peak or band areas is a recurring task in scientific data evaluation. For\r\nexample, in molecular spectroscopy, absorption line or band areas are often used to deter-\r\nmine substance abundance. NoisySignalIntegration.jl provides functionality to evaluate such\r\nsignal areas and associated uncertainties using a Monte-Carlo approach. Uncertainties may\r\ninclude contributions from (potentially correlated) Gaussian noise, baseline subtraction, and\r\nuncertainty in placing integration bounds. Uncertain integration bounds can be defined in\r\nseveral ways to constrain the integration based on the physical system under investigation\r\n(asymmetric signals, symmetric signals, signals with identical width). The package thus offers\r\na more objective uncertainty evaluation than a statement based on experience or laborious\r\nmanual analysis (Gottschalk et al., 2018).\r\nNoisySignalIntegration.jl includes a detailed documentation that covers the typical workflow\r\nwith several examples. The API uses custom datatypes and convenience functions to aid\r\nthe data analysis and permits flexible customizations: Any probability distribution from Dis-\r\ntributions.jl (Besançon et al., 2021; Lin et al., 2019) is a valid input to express uncertainty\r\nin integration bounds, thus allowing to adapt the uncertainty analysis as needed to ones\r\nstate of knowledge. The core integration function can be swapped if the included trapezoidal\r\nintegration is deemed unsatisfactory in terms of accuracy. The package uses MonteCarloMea-\r\nsurements.jl (Bagge Carlson, 2020) to express uncertain numbers which enables immediate\r\nuncertainty propagation."],["dc.identifier.doi","10.21105/joss.03526"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/106929"],["dc.language.iso","en"],["dc.relatedmaterial.material","https://zenodo.org/record/5338743"],["dc.relatedmaterial.material","https://github.com/nluetts/NoisySignalIntegration.jl"],["dc.relation.issn","2475-9066"],["dc.relation.orgunit","Institut für Physikalische Chemie"],["dc.relation.workinggroup","RG Suhm"],["dc.rights","CC BY 4.0"],["dc.subject.gro","chemistry"],["dc.subject.gro","physics"],["dc.subject.gro","measurement uncertainty"],["dc.subject.gro","noisy data"],["dc.subject.gro","numeric integration"],["dc.title","NoisySignalIntegration.jl: A Julia package for uncertainty evaluation of numeric integrals"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]