Bayesian nonparametric approaches for roc curve inference

dc.date.accessioned2018-11-29T15:36:47Z
dc.date.accessioned2022-10-18T21:27:31Z
dc.date.available2018-11-29T15:36:47Z
dc.date.available2022-10-18T21:27:31Z
dc.date.created2018-11-29T15:36:47Z
dc.date.issued2015
dc.identifierhttp://hdl.handle.net/10533/228509
dc.identifier1141193
dc.identifierWOS:000376610800017
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/4459865
dc.description.abstractThe development of medical diagnostic tests is of great importance in clinical practice, public health, and medical research. The receiver operating characteristic (ROC) curve is a popular tool for evaluating the accuracy of such tests. We review Bayesia
dc.languageeng
dc.publisherMitra, R.; Mueller, P.
dc.relationhttps://pdfs.semanticscholar.org/9623/b605f2c5dc80b35f9c3f8a4803d079546946.pdf?_ga=2.32509949.250404332.1541440337-2142829917.1531499295
dc.relationhandle/10533/111556
dc.relation10.1007/978-3-319-19518-6_16
dc.relationhandle/10533/111541
dc.relationhandle/10533/108045
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 Chile
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/3.0/cl/
dc.titleBayesian nonparametric approaches for roc curve inference
dc.typeArticulo


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