Montag, 19. November 2018, 16:45 - 17:45 iCal

ISOR Colloquium

"Robust estimators of maximum association"

Speaker: Peter Filzmoser (TU Vienna)

HS 7 (#1.303), 1st floor
Oskar-Morgenstern-Platz 1, 1090 Wien


The maximum association between two multivariate variables X and Y is defined as the maximal value that a bivariate association measure between one-dimensional projections a'X and b'Y can attain. Taking the Pearson correlation as projection index results in the first canonical correlation coefficient. We propose to use more robust association measures, such as Spearman's or Kendall's rank correlation, or association measures derived from bivariate scatter matrices. We study the robustness of the proposed maximum association measures and the corresponding estimators of the coefficients yielding the maximum association. In the important special case of Y being univariate, maximum rank correlation estimators yield regression estimators that are invariant against monotonic transformations of the response. We obtain asymptotic variances for this special case. It turns out that maximum rank correlation estimators combine good efficiency and robustness properties. Simulations and a real data example illustrate the robustness and the power for handling nonlinear relationships of these estimators.

Zur Webseite der Veranstaltung


Institut für Statistik und Operations Research


Mag. Vera Lehmwald
Fakultät für Wirtschaftswissenschaften
Institut für Statistik und Operations Research
+43 1 4277 38651