Analysis of Window-Observation Recurrence Data Zuo, Jianying Meeker, William Meeker, William Wu, Huaiqing
dc.contributor.department Statistics 2018-02-16T05:06:51.000 2020-07-02T06:56:02Z 2020-07-02T06:56:02Z 2005-06-30
dc.description.abstract <p>Many systems experience recurrent events. Recurrence data are collected to analyze quantities of interest, such as the mean cumulative number of events or the mean cumulative cost of events. Methods of analysis are available for recurrence data with left and/or right censoring. Due to practical constraints, however, recurrence data are sometimes recorded only in windows with gaps between the windows. This paper extends existing methods, both nonparametric and parametric, to windowobservation recurrence data. The nonparametric estimator requires minimum assumptions, but will be biased if the size of the risk set is not positive over the entire period of interest. There is no such difficulty when using a parametric model for the recurrence data. For cases in which the size of the risk set is zero for some periods of time, we propose a simple method that uses a parametric adjustment to the nonparametric estimator. The methods are illustrated with two numerical examples.</p>
dc.description.comments <p>This preprint was published in <em>Technometrics</em> 50 (2008): 128–143, doi:<a href="" target="_blank">10.1198/004017008000000091</a>.</p>
dc.identifier archive/
dc.identifier.articleid 1025
dc.identifier.contextkey 6996925
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath stat_las_preprints/15
dc.language.iso en
dc.source.bitstream archive/|||Fri Jan 14 20:31:38 UTC 2022
dc.source.uri 10.1198/004017008000000091
dc.subject.disciplines Statistics and Probability
dc.subject.keywords Forecast
dc.subject.keywords Mean cumulative function
dc.subject.keywords Nonhomogeneous Poisson process
dc.subject.keywords Nonparametric estimation
dc.subject.keywords Repairable system data
dc.title Analysis of Window-Observation Recurrence Data
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isAuthorOfPublication a1ae45d5-fca5-4709-bed9-3dd8efdba54e
relation.isOrgUnitOfPublication 264904d9-9e66-4169-8e11-034e537ddbca
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