Multivariate quantiles with both overall and directional probability interpretation

Hlubinka Daniel; Kotik Lukas; Siman Miroslav

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Multivariate quantiles with both overall and directional probability interpretation

机译：Multivariate quantiles with both overall and directional probability interpretation

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摘要

The article introduces multivariate quantiles (or reference regions) that have both overall and directional probability interpretation and need not be necessarily convex. They are defined by means of univariate conditional quantiles along the rays starting at a suitable central point. Their basic properties are investigated, their sample estimators and regression extensions are proposed, and their use is illustrated with both simulated and real data.

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来源
《scandinavian journal of statistics》 |2022年第4期|1586-1604|共19页
作者
Hlubinka Daniel; Kotik Lukas; Siman Miroslav;
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作者单位

Charles Univ Prague;

Natl Radiat Protect Inst;

Czech Acad Sci;

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原文格式 PDF
正文语种英语
中图分类
关键词
directional quantile; kernel estimation; multivariate quantile; nonconvex quantile; quantile regression; reference region; tolerance region; OUTPUT REGRESSION QUANTILES; CONDITIONAL QUANTILE; BAHADUR REPRESENTATION; L-1 OPTIMIZATION; DEPTH;

Multivariate quantiles with both overall and directional probability interpretation

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