Improving the Small-sample Efficiency of a Robust Correlation Matrix: A Note

Simple item page
dc.contributor.authorBlankmeyer, Eric
dc.date.accessioned2007-04-23T10:21:54Z
dc.date.available2012-02-24T10:21:54Z
dc.date.issued2007-04
dc.description.abstractThis paper reports small-sample simulations of a correlation matrix estimated robustly by P. J. Rousseeuw's MCD algorithm. It appears that the statistical efficiency of MCD can be improved significantly if a pairwise-difference transformation is first applied to the data.
dc.description.departmentFinance and Economics
dc.formatText
dc.format.extent5 pages
dc.format.medium1 file (.pdf)
dc.identifier.citationBlankmeyer, E. (2007). Improving the small-sample efficiency of a robust correlation matrix: A note. Texas State University-San Marcos, San Marcos, Texas.
dc.identifier.urihttps://hdl.handle.net/10877/4104
dc.language.isoen
dc.publisherTexas State University-San Marcos
dc.subjectcorrelation matrix
dc.subjectrobustness
dc.subjectefficiency
dc.titleImproving the Small-sample Efficiency of a Robust Correlation Matrix: A Note
dc.typePaper

Files

Original bundle

Now showing 1 - 1 of 1
Thumbnail Image
Name:
fulltext.pdf
Size:
92.93 KB
Format:
Adobe Portable Document Format
Download

Collections

McCoy College of Business