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dc.contributor.authorVidakovic, Branien_US
dc.date.accessioned2009-01-29T14:54:19Z-
dc.date.available2009-01-29T14:54:19Z-
dc.date.issued2004en_US
dc.identifier.urihttp://hdl.handle.net/10419/22199-
dc.description.abstractIt is not an overstatement to say that statistics is based on various transformations of data. Basic statistical summaries such as the sample mean, variance, z-scores, histograms, etc., are all transformed data. Some more advanced summaries, such as principal components, periodograms, empirical characteristic functions, etc., are also examples of transformed data. To give a just coverage of transforms utilized in statistics will take a size of a monograph. In this chapter we will focus only on several important transforms with the emphasis on novel multiscale transforms (wavelet transforms and its relatives).en_US
dc.language.isoengen_US
dc.publisheren_US
dc.relation.ispartofseriesPapers / Humboldt-Universität Berlin, Center for Applied Statistics and Economics (CASE) 2004,26en_US
dc.subject.ddc330en_US
dc.titleTransforms in Statisticsen_US
dc.typeWorking Paperen_US
dc.identifier.ppn495308161en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungen-
dc.identifier.repecRePEc:zbw:caseps:200426-
Appears in Collections:Papers, CASE - Center for Applied Statistics and Economics, HU Berlin

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