Calibrating the Degrees of Freedom for Automatic Data Smoothing and Effective Curve Checking

58 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Optimal Geostatistical Model Selection (2007, background): “(e.g., Cleveland and Devlin 1988; Loader 1999; Zhang 2003), which is unbiased if and only if E(BλZ|S) = S.”
Local polynomial regression on unknown manifolds (2007, background): “Using a result from [23], it can be shown that”
Testing for the equality of k regression curves (2007, background): “Some interesting comments about the choice of the smoothing parameter in testing problems can be found in Zhang (2003) .”
An updated review of Goodness-of-Fit tests for regression models (2013, methodology): “Although the literature is relatively scarce on this topic, it is worth citing the works by Kulasekera and Wang (1997), Zhang (2003, 2004) or more recently, Gao and Gijbels (2008).”
Optimal Model Assessment, Selection, and Combination (2006, background): “Zhang (2003) considered calibrating degrees of freedom for linear smoothers.”
Nonparametric Inferences for Additive Models (2005, methodology): “An alternative approximation of the null distribution can be obtained by using a calibration idea of Zhang (2003).”