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Please use this identifier to cite or link to this item:
http://hdl.handle.net/10419/22199
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Full metadata record
| DC Field | | Value | | Language |
| dc.contributor.author | | Vidakovic, Brani | | en_US |
| dc.date.accessioned | | 2009-01-29T14:54:19Z | | - |
| dc.date.available | | 2009-01-29T14:54:19Z | | - |
| dc.date.issued | | 2004 | | en_US |
| dc.identifier.uri | | http://hdl.handle.net/10419/22199 | | - |
| dc.description.abstract | | It 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.iso | | eng | | en_US |
| dc.publisher | | | | en_US |
| dc.relation.ispartofseries | | Papers / Humboldt-Universität Berlin, Center for Applied Statistics and Economics (CASE) 2004,26 | | en_US |
| dc.subject.ddc | | 330 | | en_US |
| dc.title | | Transforms in Statistics | | en_US |
| dc.type | | Working Paper | | en_US |
| dc.identifier.ppn | | 495308161 | | en_US |
| dc.rights | | http://www.econstor.eu/dspace/Nutzungsbedingungen | | - |
| dc.identifier.repec | | RePEc:zbw:caseps:200426 | | - |
| Appears in Collections: | | Papers, CASE - Center for Applied Statistics and Economics, HU Berlin
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