Computing multiple-output regression quantile regions
نویسندگان
چکیده
منابع مشابه
Computing multiple-output regression quantile regions
A procedure relying on linear programming techniques is developed to compute (regression) quantile regions that have been defined recently. In the location case, this procedure allows for computing halfspace depth regions even beyond dimension two. The corresponding algorithm is described in detail, and illustrations are provided both for simulated and real data. The efficiency of a Matlab impl...
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In the multiple-output regression context, Hallin, Paindaveine and Šiman (2010) introduced a powerful data-analytical tool based on regression quantile regions. However, the computation of these regions, that are obtained by considering in all directions an original concept of directional regression quantiles, is a very challenging problem. Paindaveine and Šiman (2010b) described a first elegan...
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A new quantile regression concept, based on a directional version of Koenker and Bassett's traditional single-output one, has been introduced in [Hallin, Paindaveine andŠiman, Annals of Statistics 2010, 635-703] for multiple-output regression problems. The polyhe-dral contours provided by the empirical counterpart of that concept, however, cannot adapt to nonlinear and/or heteroskedastic depend...
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ژورنال
عنوان ژورنال: Computational Statistics & Data Analysis
سال: 2012
ISSN: 0167-9473
DOI: 10.1016/j.csda.2010.11.014