Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/16123
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | NYSEN, Ruth | - |
dc.contributor.author | AERTS, Marc | - |
dc.contributor.author | FAES, Christel | - |
dc.date.accessioned | 2014-01-10T10:32:40Z | - |
dc.date.available | 2014-01-10T10:32:40Z | - |
dc.date.issued | 2013 | - |
dc.identifier.citation | Muggeo, Vito M.R.; Capursi, Vincenza; Boscaino, Giovanni; Lovison, Gianfranco (Ed.). Proceedings of the 28th International Workshop on Statistical Modelling Volume 1, p. 307-312 | - |
dc.identifier.isbn | 978-88-96251-47-8 | - |
dc.identifier.uri | http://hdl.handle.net/1942/16123 | - |
dc.description.abstract | Quantiles are of interest in food safety data dealing with a limit of detection. The limit of detection introduces a lot of uncertainty in the left tail of the underlying distribution, making quantile estimation for this part of the distribution difficult. Therefore we fit a model to the data and derive the model-based estimate for the quantile. Since the true distribution is unknown, model averaging is used to combine information from a set of models. In this paper we discuss two approaches to use model averaging for quantiles. The methods are applied to a data example and compared in a simulation study. The effect of an increasing percentage of censoring on the estimates is explored. | - |
dc.language.iso | en | - |
dc.publisher | Istituto Poligrafico Europeo | - |
dc.subject.other | Censoring; Model averaging; Quantiles | - |
dc.title | Model averaging quantiles for censored data | - |
dc.type | Proceedings Paper | - |
local.bibliographicCitation.authors | Muggeo, Vito M.R. | - |
local.bibliographicCitation.authors | Capursi, Vincenza | - |
local.bibliographicCitation.authors | Boscaino, Giovanni | - |
local.bibliographicCitation.authors | Lovison, Gianfranco | - |
local.bibliographicCitation.conferencedate | 8 July 2013 - 12 July 2013 | - |
local.bibliographicCitation.conferencename | 28th International Workshop on Statistical Modelling | - |
local.bibliographicCitation.conferenceplace | Palermo, Italy | - |
dc.identifier.epage | 312 | - |
dc.identifier.spage | 307 | - |
local.bibliographicCitation.jcat | C1 | - |
local.publisher.place | Palermo, Italy | - |
dc.relation.references | Burnham, K.P. and Anderson, R.A. (1998). Model selection and inference: A practical information-theoretic approach. New York: Springer-Verlag. Fenton, V.M. and Gallant, A.R. (1996). Qualitative and asymptotic performance of SNP density estimators. Journal of Econometrics, 74, 77 - 118. Gallant, A.R. and Nychka, D.W. (1987) Semi-nonparametric maximum likelihood estimation. Econometrica, 55(2), 363 - 390. Nysen, R., Aerts, M. and Faes, C. (2012), Testing goodness of fit of parametric models for censored data. Statistics in Medicine, 31, 2374 - 2385. | - |
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 | NYSEN, Ruth; AERTS, Marc & FAES, Christel (2013) Model averaging quantiles for censored data. In: Muggeo, Vito M.R.; Capursi, Vincenza; Boscaino, Giovanni; Lovison, Gianfranco (Ed.). Proceedings of the 28th International Workshop on Statistical Modelling Volume 1, p. 307-312. | - |
item.contributor | NYSEN, Ruth | - |
item.contributor | AERTS, Marc | - |
item.contributor | FAES, Christel | - |
item.fulltext | With Fulltext | - |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
NysenAertsFaes2013.pdf | Peer-reviewed author version | 241.37 kB | Adobe PDF | View/Open |
Page view(s)
12
checked on Jun 21, 2022
Download(s)
10
checked on Jun 21, 2022
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.