## Theory and Applications of Recent Robust MethodsMia Hubert, Greet Pison, Anja Struyf, Stefan Van Aelst Springer Science & Business Media, 2004 M06 25 - 400 pages The International Conference for Robust Statistics 2003, ICORS 2003, took place at the University of Antwerp, Belgium, from July 13-18. The conference was intended to be a forum where all aspects of robust statistics could be discussed. As such the scientific program included a wide range of talks on new developments and practice of robust statistics, with applications to finance, chemistry, engineering, and other fields. Of equal interest were interactions between robustness and other fields of statistics, and science in general. This volume offers a wide range of papers that were presented at the conference. Several articles primarily contain new methods and theoretical results, while others investigate empirical properties, discuss computational aspects, or emphasize applications of robust methods. Many contributions contain links to other fields, such as computer vision, computational geometry, chemometrics and finance. Intended for both researchers and practitioners, this book will be a valuable resource for studying and applying recent robust statistical methods. |

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### Contents

III | 1 |

IV | 13 |

V | 27 |

VI | 39 |

VII | 49 |

VIII | 59 |

IX | 71 |

X | 83 |

XXI | 207 |

XXII | 221 |

XXIII | 235 |

XXIV | 247 |

XXV | 259 |

XXVI | 271 |

XXVII | 283 |

XXVIII | 297 |

XI | 93 |

XII | 105 |

XIII | 119 |

XIV | 131 |

XV | 141 |

XVI | 153 |

XVII | 165 |

XVIII | 173 |

XIX | 183 |

XX | 195 |

XXIX | 307 |

XXX | 319 |

XXXI | 329 |

XXXII | 343 |

XXXIII | 355 |

XXXIV | 367 |

XXXV | 377 |

XXXVI | 387 |

### Other editions - View all

Theory and Applications of Recent Robust Methods Mia Hubert,Greet Pison,Anja Struyf,Stefan Van Aelst Limited preview - 2012 |

Theory and Applications of Recent Robust Methods Mia Hubert,Greet Pison,Anja Struyf,Stefan Van Aelst No preview available - 2004 |

Theory and Applications of Recent Robust Methods Mia Hubert,Greet Pison,Anja Struyf No preview available - 2004 |

### Common terms and phrases

algorithm alternative analysis applied approach approximation assume asymptotic bounded breakdown point called classical components compute conditional consider consistency constant contamination corresponding covariance matrix data set defined definition denote density depend depth distance distribution efficiency empirical equal error et al example exists expected Figure function given increasing independent influence introduced known least likelihood limiting linear Mathematics maximum mean measures median methods minimization multivariate normal distribution Note observations obtained outliers parameters performance plot positive possible present probability problem procedure properties proposed quadratic quantile random References regression residuals respectively returns robust estimators Rousseeuw sample scale selection shows simple simulation skewness smoothed solution Squares standard Statist structure Table tail technique tion transformation trimmed variables variance vector weight