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.File | Dimensione | Formato | |
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