Abstract
Local polynomial regression is a convenient method for smoothing scatterplots with readily available software. However, it is well known that variable amounts of bias are induced by the smoothing operation. This article proposes a simple visualization tool based on approximate confidence intervals which can alert the data analyst to regions of the regression function domain which might be susceptible to unacceptably large levels of bias, and possibly indicating a need for a less automatic smoothing approach. A simulation study verifies the accuracy of the confidence bands, and the method is illustrated with several real datasets.
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