Given n joint observations on k continuous variables, mcd.src computes a robust mean vector and a robust covariance matrix using the minimum covariance determinant algorithm [P. J. Rousseeuw and A. M. Leroy (1987), Robust Regression and Outlier Detection, New York: Wiley]. Observations whose robust Mahalanobis distances exceed the 97.5% chi-square value with k degrees of freedom are flagged as potential outliers. mcd.src uses a resampling method, and the number of subsamples (each having k+1 data) is the procedure's only option (default = 3000 subsamples). mcd.src reads the data as series whose first observation is start and whose last observation is end (i. e., n = end - start + 1).
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Publisher Info
Software component provided by Boston College Department of Economics in its series Statistical Software Components with number
R931601.
Size: Programming language: RATS Requires: Date of creation: 16 Mar 1999 Date of revision: Handle: RePEc:boc:bocode:r931601
Contact details of provider: Postal: Boston College, 140 Commonwealth Avenue, Chestnut Hill MA 02467 USA Phone: 617-552-3670 Fax: +1-617-552-2308 Email: Web page: http://fmwww.bc.edu/EC/ More information through EDIRC
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