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Geoadditive regression modeling of stream biological condition

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dc.contributor.author Schmid, Matthias en
dc.contributor.author Hothorn, Torsten en
dc.contributor.author Maloney, Kelly O. en
dc.contributor.author Weller, Donald E. en
dc.contributor.author Potapov, Sergej en
dc.date.accessioned 2012-07-02T14:58:43Z
dc.date.available 2012-07-02T14:58:43Z
dc.date.issued 2011
dc.identifier.citation Schmid, Matthias, Hothorn, Torsten, Maloney, Kelly O., Weller, Donald E., and Potapov, Sergej. 2011. "<a href="https://repository.si.edu/handle/10088/18568">Geoadditive regression modeling of stream biological condition</a>." <em>Environmental and Ecological Statistics</em>. 18 (4):709&ndash;733. <a href="https://doi.org/10.1007/s10651-010-0158-4">https://doi.org/10.1007/s10651-010-0158-4</a> en
dc.identifier.issn 1352-8505
dc.identifier.uri http://hdl.handle.net/10088/18568
dc.description.abstract Indices of biotic integrity have become an established tool to quantify the condition of small non-tidal streams and their watersheds. To investigate the effects of watershed characteristics on stream biological condition, we present a new technique for regressing IBIs on watershed-specific explanatory variables. Since IBIs are typically evaluated on an ordinal scale, our method is based on the proportional odds model for ordinal outcomes. To avoid overfitting, we do not use classical maximum likelihood estimation but a component-wise functional gradient boosting approach. Because component-wise gradient boosting has an intrinsic mechanism for variable selection and model choice, determinants of biotic integrity can be identified. In addition, the method offers a relatively simple way to account for spatial correlation in ecological data. An analysis of the Maryland Biological Streams Survey shows that nonlinear effects of predictor variables on stream condition can be quantified while, in addition, accurate predictions of biological condition at unsurveyed locations are obtained. en
dc.relation.ispartof Environmental and Ecological Statistics en
dc.title Geoadditive regression modeling of stream biological condition en
dc.type Journal Article en
dc.identifier.srbnumber 109458
dc.identifier.doi 10.1007/s10651-010-0158-4
rft.jtitle Environmental and Ecological Statistics
rft.volume 18
rft.issue 4
rft.spage 709
rft.epage 733
dc.description.SIUnit SERC en
dc.description.SIUnit Peer-reviewed en
dc.citation.spage 709
dc.citation.epage 733


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