Minimum Covariance Determinant Estimator

1. P. J. Rousseeuw and K. van Driessen (1999) A fast algorithm for the minimum covariance determinant estimator. (Web site)

Statistics

1. Rousseeuw and Croux (1993) proposed two new statistics as alternatives to the MAD statistic.

Kaufman

1. The original Fortran programs carried out new cluster analysis algorithms introduced in the book of Kaufman and Rousseeuw (1990).

Cluster Analysis

1. Rousseeuw, P.J., A graphical aid to the interpretations and validation of cluster analysis, J. Compu.
2. Kaufmann, L. and Rousseeuw, P. J. 1990. Finding groups in data: an introduction to cluster analysis. (Web site)

Robust Estimators

1. It is better to use distances based on robust estimators of multivariate location and scatter (Rousseeuw and Leroy 1987, pp.

Robust Estimator

1. As a robust estimator of location and scatter, we use the minimum covariance determinant (MCD) estimator of Rousseeuw.
2. The minimum covariance determinant (MCD) method of Rousseeuw is a highly robust estimator of multivariate location and scatter.

Rousseeuw

1. Rousseeuw, P. J. (1987). Silhouettes: a graphical aid to the interpretation and validation of cluster analysis.
2. Good books on robust statistics include those by Huber (1981), Hampel et al (1986) and Rousseeuw and Leroy (1987). (Web site)
3. Croux C. and P. Rousseeuw, Time-efficient algorithms for two highly robust estimators of scale, Computational Statistics, Physica-Verlag, 1, 411-428, 1992. (Web site)

Categories

1. Silhouettes
2. Robust Estimator
3. Computer Science > Artificial Intelligence > Data Mining > Cluster Analysis
4. Mcd
5. Computational Statistics
6. Books about "Rousseeuw" in Amazon.com
   

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