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http://hdl.handle.net/1942/16117
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DC Field | Value | Language |
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dc.contributor.author | JASPERS, Stijn | - |
dc.contributor.author | AERTS, Marc | - |
dc.contributor.author | VERBEKE, Geert | - |
dc.date.accessioned | 2014-01-10T09:41:54Z | - |
dc.date.available | 2014-01-10T09:41:54Z | - |
dc.date.issued | 2013 | - |
dc.identifier.citation | Muggeo,V.M.R.; Capursi, V.; Boscaino, G.; Lovison G. (Ed.). Proceedings of the 28th International Workshop on Statistical Modelling, Volume.1, p. 191-196 | - |
dc.identifier.isbn | 978-88-96251-47-8 | - |
dc.identifier.uri | http://hdl.handle.net/1942/16117 | - |
dc.description.abstract | Antimicrobial resistance has become one of the main public health burdens of the last decades, and monitoring the development and spread of non-wild-type isolates has therefore gained increased interest. Monitoring is performed, based on the Minimum Inhibition Concentration (MIC) values, which are collected through the application of dilution experiments. A semi-parametric mixture model is presented, which is able to estimate the full continuous MIC distribution. The model is based on an extended and censored-adjusted version of the penalized mixture approach often used in density estimation. A data application and simulation study are presented in which the promising behaviour of the new method is illustrated. | - |
dc.language.iso | en | - |
dc.publisher | Istituto Poligrafico Europeo | - |
dc.subject.other | Antimicrobial resistance; Censoring; Penalized mixture approach; Semi-parametric | - |
dc.title | Estimation of an MIC distribution using a two-stage semi-parametric mixture model | - |
dc.type | Proceedings Paper | - |
local.bibliographicCitation.authors | Muggeo,V.M.R. | - |
local.bibliographicCitation.authors | Capursi, V. | - |
local.bibliographicCitation.authors | Boscaino, G. | - |
local.bibliographicCitation.authors | Lovison G. | - |
local.bibliographicCitation.conferencedate | July 8-12 2013 | - |
local.bibliographicCitation.conferencename | 28th International Workshop on Statistical Modelling | - |
local.bibliographicCitation.conferenceplace | Palermo | - |
dc.identifier.epage | 196 | - |
dc.identifier.spage | 191 | - |
local.bibliographicCitation.jcat | C1 | - |
local.publisher.place | Palermo | - |
dc.relation.references | Eilers, P. and Marx, B. (1996). Flexible smoothing with b-splines and penalties. Statistical Science, 11, 89 - 121. Schellhase, C. and Kauermann, G. (2012). Density estimation and comparison with a penalized mixture approach. Computational Statistics, 27, 757 - 777. | - |
local.type.refereed | Refereed | - |
local.type.specified | Proceedings Paper | - |
local.bibliographicCitation.btitle | Proceedings of the 28th International Workshop on Statistical Modelling, Volume.1 | - |
item.accessRights | Open Access | - |
item.fullcitation | JASPERS, Stijn; AERTS, Marc & VERBEKE, Geert (2013) Estimation of an MIC distribution using a two-stage semi-parametric mixture model. In: Muggeo,V.M.R.; Capursi, V.; Boscaino, G.; Lovison G. (Ed.). Proceedings of the 28th International Workshop on Statistical Modelling, Volume.1, p. 191-196. | - |
item.contributor | JASPERS, Stijn | - |
item.contributor | AERTS, Marc | - |
item.contributor | VERBEKE, Geert | - |
item.fulltext | With Fulltext | - |
Appears in Collections: | Research publications |
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File | Description | Size | Format | |
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Jaspers_IWSM28.pdf | Peer-reviewed author version | 321.42 kB | Adobe PDF | View/Open |
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