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dc.contributor.authorLind, Jo Thori
dc.date.accessioned2011-11-26T15:23:06Z
dc.date.available2011-11-26T15:23:06Z
dc.date.issued2002
dc.identifier.issn1892-753x
dc.identifier.urihttp://hdl.handle.net/11250/180413
dc.description.abstractAbstract: The time series nature of repeated surveys is seldom taken into account. I present a statistical model of repeated surveys and construct a computationally feasible estimator based on the Kalman filter. The novelty is that the estimator efficiently uses the whole underlying data set. However, for computational purposes, we only need the first and second empirical moments of the data. Keywords: Surveys, Kalman filter, time series.no_NO
dc.language.isoengno_NO
dc.publisherStatistics Norway, Research Departmentno_NO
dc.relation.ispartofseriesDiscussion Papers;No. 333
dc.subjectTime seriesno_NO
dc.subjectKalman filterno_NO
dc.subjectJEL classification: C22no_NO
dc.subjectJEL classification: C53no_NO
dc.subjectJEL classification: C81no_NO
dc.titleSmall continuous surveys and the Kalman filterno_NO
dc.typeWorking paperno_NO
dc.subject.nsiVDP::Mathematics and natural science: 400::Mathematics: 410::Statistics: 412no_NO
dc.source.pagenumber17 s.no_NO


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