Please use this identifier to cite or link to this item: https://doi.org/10.1007/s10463-009-0224-6
DC FieldValue
dc.titleAnalysis of rounded data from dependent sequences
dc.contributor.authorZhang, B.
dc.contributor.authorLiu, T.
dc.contributor.authorBai, Z.D.
dc.date.accessioned2014-10-28T05:10:04Z
dc.date.available2014-10-28T05:10:04Z
dc.date.issued2010-12
dc.identifier.citationZhang, B., Liu, T., Bai, Z.D. (2010-12). Analysis of rounded data from dependent sequences. Annals of the Institute of Statistical Mathematics 62 (6) : 1143-1173. ScholarBank@NUS Repository. https://doi.org/10.1007/s10463-009-0224-6
dc.identifier.issn00203157
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/105003
dc.description.abstractObservations on continuous populations are often rounded when recorded due to the precision of the recording mechanism. However, classical statistical approaches have ignored the effect caused by the rounding errors. When the observations are independent and identically distributed, the exact maximum likelihood estimation (MLE) can be employed. However, if rounded data are from a dependent structure, the MLE of the parameters is difficult to calculate since the integral involved in the likelihood equation is intractable. This paper presents and examines a new approach to the parameter estimation, named as "short, overlapping series" (SOS), to deal with the α-mixing models in presence of rounding errors. We will establish the asymptotic properties of the SOS estimators when the innovations are normally distributed. Comparisons of this new approach with other existing techniques in the literature are also made by simulation with samples of moderate sizes. © 2009 The Institute of Statistical Mathematics, Tokyo.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/s10463-009-0224-6
dc.sourceScopus
dc.subjectARMA(p, q) model
dc.subjectBRB corrections
dc.subjectRounded data
dc.subjectSheppard corrections
dc.subjectSOS estimation
dc.typeArticle
dc.contributor.departmentSTATISTICS & APPLIED PROBABILITY
dc.description.doi10.1007/s10463-009-0224-6
dc.description.sourcetitleAnnals of the Institute of Statistical Mathematics
dc.description.volume62
dc.description.issue6
dc.description.page1143-1173
dc.description.codenAISXA
dc.identifier.isiut000282693800006
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