Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/16123
Title: Model averaging quantiles for censored data
Authors: NYSEN, Ruth 
AERTS, Marc 
FAES, Christel 
Issue Date: 2013
Publisher: Istituto Poligrafico Europeo
Source: 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
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.
Keywords: Censoring; Model averaging; Quantiles
Document URI: http://hdl.handle.net/1942/16123
ISBN: 978-88-96251-47-8
Category: C1
Type: Proceedings Paper
Appears in Collections:Research publications

Files in This Item:
File Description SizeFormat 
NysenAertsFaes2013.pdfMain article241.37 kBAdobe PDFView/Open
Show full item record

Page view(s)

12
checked on May 22, 2022

Download(s)

10
checked on May 22, 2022

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.