Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Chen, LA | en_US |
dc.contributor.author | Welsh, AH | en_US |
dc.date.accessioned | 2014-12-08T15:41:51Z | - |
dc.date.available | 2014-12-08T15:41:51Z | - |
dc.date.issued | 2002-10-01 | en_US |
dc.identifier.issn | 0047-259X | en_US |
dc.identifier.uri | http://dx.doi.org/10.1006/jmva.2001.2043 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/28467 | - |
dc.description.abstract | We introduce bivariate quantiles which are defined through the bivariate distribution function. This approach ensures that, unlike most multivariate medians or the multivariate M-quartiles, the bivariate quantiles satisfy an analogous property to that of the univariate quantiles in that they partition R-2 into sets with a specified probability content. The definition of bivariate quantiles leads naturally to the definition of quantities such as the bivariate median, bivariate extremes, the bivariate quantile curve, and the bivariate trimmed mean. We also develop asymptotic representations for the bivariate quantiles. (C) 2002 Elsevier Science (USA). | en_US |
dc.language.iso | en_US | en_US |
dc.subject | bivariate extreme | en_US |
dc.subject | bivariate median | en_US |
dc.subject | bivariate quantile | en_US |
dc.subject | bivariate quantile curve | en_US |
dc.subject | bivariate trimmed mean | en_US |
dc.title | Distribution-function-based bivariate quantiles | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1006/jmva.2001.2043 | en_US |
dc.identifier.journal | JOURNAL OF MULTIVARIATE ANALYSIS | en_US |
dc.citation.volume | 83 | en_US |
dc.citation.issue | 1 | en_US |
dc.citation.spage | 208 | en_US |
dc.citation.epage | 231 | en_US |
dc.contributor.department | 交大名義發表 | zh_TW |
dc.contributor.department | National Chiao Tung University | en_US |
dc.identifier.wosnumber | WOS:000178596700010 | - |
dc.citation.woscount | 5 | - |
Appears in Collections: | Articles |
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