An Object-Oriented Framework for Robust Multivariate Analysis

Untitled work

(1994) · Cited by 21,711

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Gabriel, K. R. (1971) · Biometrika · doi:10.1093/biomet/58.3.453 · Cited by 3,088

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Lachenbruch, P. A., & Mickey, M. R. (1968) · Technometrics · doi:10.1080/00401706.1968.10490530 · Cited by 1,560

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Lachenbruch, P. A., & Goldstein, M. (1979) · Encyclopedia of Statistical Sciences · doi:10.1002/0471667196.ess0507 · Cited by 1,314

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Rousseeuw, P. J. (1985) · Springer eBooks · doi:10.1007/978-94-009-5438-0_20 · Cited by 1,122

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Gnanadesikan, R., & Kettenring, J. R. (1972) · Biometrics · doi:10.2307/2528963 · Cited by 826

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Devlin, S. J., Gnanadesikan, R., & Kettenring, J. R. (1981) · Journal of the American Statistical Association · doi:10.1080/01621459.1981.10477654 · Cited by 373

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Locantore, N., Marron, J. S., Simpson, D. G., Tripoli, N., Zhang, J. T., Cohen, K. L., Boente, G., Fraiman, R., Brumback, B., Croux, C., et al. (1999) · Test · doi:10.1007/bf02595862 · Cited by 367

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Naga, R. A., & Antille, G. (1990) · Computational Statistics & Data Analysis · doi:10.1016/0167-9473(90)90062-m · Cited by 19

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Todorov, V., Neykov, N. M., & Neytchev, P. (1990) · Physica-Verlag eBooks · doi:10.1007/978-3-642-50096-1_30 · Cited by 13

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FILZMOSER P.: An object oriented framework for robust multivariate analysis

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