MCD: RATS module to compute robust mean vector and covariance matrix

Eric Blankmeyer ()
Additional contact information
Eric Blankmeyer: Texas State University

Statistical Software Components from Boston College Department of Economics

Abstract: 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).

Language: RATS
Keywords: robust; estimation (search for similar items in EconPapers)
Date: 1999-03-16
References: Add references at CitEc
Citations:

Downloads: (external link)
http://fmwww.bc.edu/repec/bocode/m/mcd.src program code (text/plain)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:boc:bocode:r931601

Ordering information: This software item can be ordered from
http://repec.org/docs/ssc.php

Access Statistics for this software item

More software in Statistical Software Components from Boston College Department of Economics Boston College, 140 Commonwealth Avenue, Chestnut Hill MA 02467 USA. Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F Baum ().