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In this paper, we discuss some practical computational issues for quantile regression. We consider the computation from two aspects: estimation and inference. For estimation, we cover three algorithms: simplex, interior point, and smoothing. We describe and compare these algorithms, then discuss implementation of some computing techniques, which include(More)
Nonparametric regression has been popularly used in curve fitting, signal denosing, and image processing. In such applications, the underlying functions (or signals) may vary irregularly, and it is very common that data are contaminated with outliers. Adaptive and robust techniques are needed to extract clean and accurate information. In this paper, we(More)
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