We discuss nonparametric estimation of conditional quantiles of a circular distribution when the conditioning variable is either linear or circular. Two different approaches are pursued: inversion of a conditional distribution function estimator, and minimization of a smoothed check function. Local constant and local linear versions of both estimators are discussed. Simulation experiments and a real data case study are used to illustrate the usefulness of the methods.

Nonparametric circular quantile regression / Di Marzio, Marco; Panzera, Agnese; Taylor, Charles C.. - In: JOURNAL OF STATISTICAL PLANNING AND INFERENCE. - ISSN 0378-3758. - STAMPA. - 170:(2016), pp. 1-14. [10.1016/j.jspi.2015.08.004]

Nonparametric circular quantile regression

PANZERA, AGNESE;
2016

Abstract

We discuss nonparametric estimation of conditional quantiles of a circular distribution when the conditioning variable is either linear or circular. Two different approaches are pursued: inversion of a conditional distribution function estimator, and minimization of a smoothed check function. Local constant and local linear versions of both estimators are discussed. Simulation experiments and a real data case study are used to illustrate the usefulness of the methods.
2016
170
1
14
Di Marzio, Marco; Panzera, Agnese; Taylor, Charles C.
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1005070
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